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Pipeline run

509084e3-a67d-4ea3-9893-2679a53c2983

Pipeline LLM cost (USD)
API 1: $0.0081 API 2: $0.0002 API 3: $0.0000 Total: $0.0083

Client output enrichment

v2 Skill cluster · Nature of work · AI index · Tech stack maturity · Evidence · KRA description
role baseline loaded sources · ai_index: jd · nature_of_work: jd · tech_stack_maturity: jd
Nature of work · Data transformation and modeling
Lead data engineering, AI, and visualization teams while shaping BI strategy, delivering scalable client solutions, and running advanced analytics work like predictive modeling, machine learning, and dashboards. Also manage resources, timelines, and team development.
"• Oversee the design and execution of advanced analytics projects, including predictive modeling, machine learning algorithms, and data visualization initiatives."
Tech stack maturity
AI-Native & Bleeding-Edge cache hit
The role centers on AI and machine learning, which most strongly aligns with an AI-native, cutting-edge technology stack.
AI index (0 = no AI use, 5 = totally AI-dependent · v2.1)
1.70 / 5
· Title match
Has AI skill
AI skill (primary)
· AI skill (secondary)
· On AI team
· Builds AI products
vocab breakdown (legacy)
Assistants (×1):
Frameworks (×2):
Models / concepts (×3): AI, Machine Learning
Evidence — skills matched in JD (6)
Data Engineering AI Data Visualization Business Intelligence Predictive Modeling Machine Learning
Skill cluster (2 dimension groups, role-scoped)
AI Governance and Model Security
Machine Learning
Cross-cutting / unaligned
Data Engineering AI Data Visualization Business Intelligence Predictive Modeling
Show KRA description ↓
• Lead and manage the Data Engineering, AI, and Visualization teams, ensuring high performance and alignment with company objectives. • Drive the development and implementation of business intelligence strategies that support business goals and provide competitive advantages. • Collaborate with cross-functional teams, including sales, marketing, and product development, to identify and capitalize on growth opportunities. • Foster a culture of continuous improvement and innovation within the teams, encouraging the adoption of new technologies and methodologies. • Develop and maintain strong relationships with key clients, understanding their needs and providing tailored business intelligence solutions. • Ensure the delivery of high-quality, scalable, and reliable data solutions that meet client expectations. • Oversee the design and execution of advanced analytics projects, including predictive modeling, machine learning algorithms, and data visualization initiatives. • Monitor industry trends and advancements in business intelligence, AI, and data engineering to keep the company at the forefront of technology. • Manage budgets, resource allocation, and project timelines, ensuring efficient operation of the Business Intelligence division. • Mentor and develop team members, providing guidance and support to foster career growth and skill development.

Signals

Skill ml-engineer
0.17
Alias
KRA data-engineer
0.56

Post-classification

Centroidupdated · n=276
Alias collision log
New-role queue
New skills captured4
New KRA captured

Captured for admin review

Data Engineering primary Data Engineer pending
Data Visualization primary Data Engineer pending
Business Intelligence primary Data Engineer pending
Predictive Modeling primary Data Engineer pending
Status: completed Created: 2026-05-27T15:17:33.277510Z Updated: 2026-06-12T16:40:11.158697Z API 3 duration: 10422 ms
Flow Current 3-step pipeline

1 POST /skills/extract-from-jd

2 POST /skills/extract-details

3 POST /skills/final-role-output

Role Chosen role & resolution

Data Engineer

domain · Data Engineering & Analytics CASE DOMAIN

slug: data-engineer · id: 2 · source: db

Domain=Data Engineering & Analytics; The role is primarily a senior leadership position overseeing data engineering and analytics delivery, with responsibilities closest to a Data Engineer leadership scope rather than a hands-on BI developer or analyst role.

Matched skills

Data EngineeringAIVisualizationbusiness intelligencepredictive modelingmachine learning algorithmsdata visualizationresource allocationbudgetproject timelines

Matched dimensions

Data Team LeadershipBusiness Intelligence StrategyCross-functional CollaborationAdvanced Analytics DeliveryClient SolutioningScalable Data SolutionsTechnology Innovation MonitoringOperational Management

Matched KRAs

Lead and manage the Data Engineering, AI, and Visualization teamsDrive the development and implementation of business intelligence strategiesCollaborate with cross-functional teamsDevelop and maintain strong relationships with key clientsEnsure the delivery of high-quality, scalable, and reliable data solutionsOversee the design and execution of advanced analytics projectsMonitor industry trends and advancementsManage budgets, resource allocation, and project timelinesMentor and develop team members

Resolution: in_db — role exists in library; skill↔dim and role↔dim links saved when applicable.

0
New skills
0
Skill↔dim saved
0
Role↔dim saved
0
Skipped

Job description

Job Title: Head of Business Intelligence || Data Engineering || BI || Data Visualization 
Location: Faridabad, Noida
Department: Business Intelligence and Data Analytics
Reports to: Vice President, Technology


Job Summary: 
We are seeking a highly skilled and dynamic Head of Business Intelligence to lead our Business Intelligence division. This role will be pivotal in managing our Data Engineering, AI, and Visualization teams. The ideal candidate will be hands-on with these functions, focusing on developing innovative solutions and driving account growth. You will play a critical role in shaping the future of our data-driven strategies and ensuring our clients receive top-tier business intelligence services.


Key Responsibilities:
• Lead and manage the Data Engineering, AI, and Visualization teams, ensuring high performance and alignment with company objectives.
• Drive the development and implementation of business intelligence strategies that support business goals and provide competitive advantages.
• Collaborate with cross-functional teams, including sales, marketing, and product development, to identify and capitalize on growth opportunities.
• Foster a culture of continuous improvement and innovation within the teams, encouraging the adoption of new technologies and methodologies.
• Develop and maintain strong relationships with key clients, understanding their needs and providing tailored business intelligence solutions.
• Ensure the delivery of high-quality, scalable, and reliable data solutions that meet client expectations.
• Oversee the design and execution of advanced analytics projects, including predictive modeling, machine learning algorithms, and data visualization initiatives.
• Monitor industry trends and advancements in business intelligence, AI, and data engineering to keep the company at the forefront of technology.
• Manage budgets, resource allocation, and project timelines, ensuring efficient operation of the Business Intelligence division.
• Mentor and develop team members, providing guidance and support to foster career growth and skill development.


Qualifications:
• Bachelor’s or Master’s degree in Computer Science, Data Science, Business Analytics, or related field.
• Minimum of 10 years’ experience in business intelligence, data engineering, or a related field, with at least 3 years in a leadership role.
• Proven track record of managing and scaling high-performing teams.
• Extensive experience with cloud-based data engineering, machine learning, AI technologies, and data visualization tools.
• Strong business acumen with a proven ability to develop strategies that drive business growth.
• Excellent communication and interpersonal skills, with the ability to engage and influence stakeholders at all levels.
• Demonstrated ability to manage complex projects and cross-functional teams.
• Deep understanding of the latest trends in business intelligence and data analytics.


About Damco
We are a global technology company with more than two decades of core IT experience. Our differentiators are technological prowess with unwavering back-end support on a wide range of technologies and industry-leading platforms.
At Damco, we take pride in building innovative, efficient, and robust IT solutions for our clients. We match the client’s business goals with our technology expertise and immaculate execution capabilities to solve issues that matter to the end-user.
Damco has developed hundreds of products and applications, redefined countless processes, built numerous technology teams and systems, and delivered significant financial results to customers from diverse verticals.
We believe in empowering our people to perform and grow by offering opportunities, learning, and inspiration—to ‘act and accomplish’. If you are a self-starter looking for an open and collaborative work culture to excel in your career, we are the place for you.

Skills from this JD

Each row merges API 1 extraction, API 2 library match / v3 orchestration (dimensions + locked dims), and API 3 persistence tags.

Data Engineering Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
AI Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: AI id=1347 · ai

Aliases — catalog

  • AI (CANONICAL)

Context tags (catalog)

AI ethics PyTorch TensorFlow algorithm optimization computer vision data preprocessing deep learning feature engineering machine learning model training natural language processing neural networks predictive analytics reinforcement learning supervised learning

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Artificial Intelligence
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: AI appears in a large and growing share of job descriptions across software, data, and product roles; major vendors like Microsoft, Google, and AWS have broad AI offerings and hiring demand reflects mainstream adoption.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1020
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Data Visualization Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Business Intelligence Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
PRACTICE
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Predictive Modeling Primary New / orchestrated API 3: new canonical path (new) New / unmatched skill (orchestrated in API 2)

Skill enrichment (orchestrator / LLM)

No Stage 7 enrichment blob on this skill (orchestrator skipped enrichment).

Derived legacy fields
Category
Data Engineering Tools
Sub-category
general
Skill nature
CONCEPT
Volatility
MEDIUM
Typical lifespan
MULTI_YEAR
Version strategy
UNVERSIONED
Machine Learning Primary Library skill API 3: existing canonical (in_db) Existing skill (matched library)
Canonical: Machine Learning id=1356 · machine-learning

Aliases — catalog

  • Machine Learning (CANONICAL)

Context tags (catalog)

Keras PyTorch TensorFlow cross-validation data preprocessing ensemble methods feature engineering hyperparameter tuning model evaluation natural language processing neural networks reinforcement learning scikit-learn supervised learning unsupervised learning

Stored enrichment (catalog DB)

Category
Concept
Sub-category
Machine Learning
Confidence
0.98
Version strategy
NOT_APPLICABLE

Maturity reasoning: Machine Learning appears in large volumes of job descriptions across data, product, and platform roles, and major cloud vendors (AWS, Google Cloud, Azure) offer dedicated ML services and certifications, indicating broad adoption.

Skill profile (library / DB)

Skill nature
CONCEPT
Volatility
STABLE
Typical lifespan
EVERGREEN
Category id
2
Sub-category id
1024
Extractable
True
Also category
False

Dimensions (API 2 worklist)

  • AI Governance and Model Security Catalog dimension db id 50

    Library dimension (catalog)

    Roles linked in library: AI Engineer, ML Engineer, MLOps Engineer

  • React Frontend Development Catalog dimension db id 96

    Library dimension (catalog)

API 3 link attempts (this skill)

Dimension Skill↔dim Role↔dim Outcome
AI Governance and Model Security
ai-governance-and-model-security
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

All API 3 persistence rows

Same grid as the skill-extractor “Persistence items” table: one row per (skill × dimension) work item.

Skill Tag Dimension Skill↔dim Role↔dim Outcome Notes
AI in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Machine Learning in_db
AI Governance and Model Security
ai-governance-and-model-security
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)
Machine Learning in_db
React Frontend Development
d_init_01
Existing dimension (library) · Role↔dimension skipped (dimension not under chosen role)

Library artifacts (this run)

Kind Detail DB id
canonical_skill_proposed Data Engineering | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Data Visualization | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Business Intelligence | type=Data Engineering Tools subtype=general nature=PRACTICE lifespan=MULTI_YEAR
canonical_skill_proposed Predictive Modeling | type=Data Engineering Tools subtype=general nature=CONCEPT lifespan=MULTI_YEAR
nano JD Parser — gpt-4.1-nano click to toggle
RoleHead of Business Intelligence
CompanyDamco
ExperienceMinimum of 10 years’ experience in business intelligence, data engineering, or a related field, with at least 3 years in a leadership role.
DomainIT Services & Consulting
Location Faridabad, India (null)
JD type pass
Show raw JSON
{
  "JD_type": "pass",
  "about_company": {
    "source_marker": {
      "first_5_words": "We are a global technology",
      "last_5_words": "to excel in your career, we are the place for you."
    },
    "text": "We are a global technology company with more than two decades of core IT experience. Our differentiators are technological prowess with unwavering back-end support on a wide range of technologies and industry-leading platforms.\nAt Damco, we take pride in building innovative, efficient, and robust IT solutions for our clients. We match the client\u2019s business goals with our technology expertise and immaculate execution capabilities to solve issues that matter to the end-user.\nDamco has developed hundreds of products and applications, redefined countless processes, built numerous technology teams and systems, and delivered significant financial results to customers from diverse verticals.\nWe believe in empowering our people to perform and grow by offering opportunities, learning, and inspiration\u2014to \u2018act and accomplish\u2019. If you are a self-starter looking for an open and collaborative work culture to excel in your career, we are the place for you.",
    "word_count": 116
  },
  "archetype_override_applied": true,
  "archetype_override_matched_skills": [
    "Algorithms",
    "Analytics",
    "Machine Learning",
    "scaling",
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    "Role",
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    "relationships",
    "goals"
  ],
  "certifications": [],
  "company_name": "Damco",
  "ctc": null,
  "domain": {
    "primary": {
      "aliases": [
        "ITES",
        "BPO",
        "Tech Consulting"
      ],
      "domain": "IT Services \u0026 Consulting"
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    "secondary": null
  },
  "education": [
    {
      "level": "Bachelor\u0027s",
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      "requirement": "required"
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  ],
  "experience": {
    "max": null,
    "min": 10,
    "raw": "Minimum of 10 years\u2019 experience in business intelligence, data engineering, or a related field, with at least 3 years in a leadership role."
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  "job_locations": [
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      "state": null,
      "work_mode": "null"
    },
    {
      "aliases": [],
      "city": "Noida",
      "country": "India",
      "state": null,
      "work_mode": "null"
    }
  ],
  "role": "Head of Business Intelligence",
  "role_aliases": [
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  "role_archetype": "Engineering",
  "roles_and_responsibilities": [
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      "bullet_count": 10,
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      "text": "\u2022 Lead and manage the Data Engineering, AI, and Visualization teams, ensuring high performance and alignment with company objectives.\n\u2022 Drive the development and implementation of business intelligence strategies that support business goals and provide competitive advantages.\n\u2022 Collaborate with cross-functional teams, including sales, marketing, and product development, to identify and capitalize on growth opportunities.\n\u2022 Foster a culture of continuous improvement and innovation within the teams, encouraging the adoption of new technologies and methodologies.\n\u2022 Develop and maintain strong relationships with key clients, understanding their needs and providing tailored business intelligence solutions.\n\u2022 Ensure the delivery of high-quality, scalable, and reliable data solutions that meet client expectations.\n\u2022 Oversee the design and execution of advanced analytics projects, including predictive modeling, machine learning algorithms, and data visualization initiatives.\n\u2022 Monitor industry trends and advancements in business intelligence, AI, and data engineering to keep the company at the forefront of technology.\n\u2022 Manage budgets, resource allocation, and project timelines, ensuring efficient operation of the Business Intelligence division.\n\u2022 Mentor and develop team members, providing guidance and support to foster career growth and skill development.",
      "word_count": 218
    }
  ],
  "urls": []
}
API 1 — extract-from-jd click to toggle
{
  "final_skills": [
    {
      "is_primary": true,
      "skill_name": "Data Engineering"
    },
    {
      "is_primary": true,
      "skill_name": "AI"
    },
    {
      "is_primary": true,
      "skill_name": "Data Visualization"
    },
    {
      "is_primary": true,
      "skill_name": "Business Intelligence"
    },
    {
      "is_primary": true,
      "skill_name": "Predictive Modeling"
    },
    {
      "is_primary": true,
      "skill_name": "Machine Learning"
    }
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  "jd_role": {
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    "rationale": null,
    "role_aliases": [
      "BI Lead",
      "Director of Business Intelligence",
      "Head of BI"
    ],
    "role_archetype": "Engineering",
    "slug": ""
  },
  "nano_parsed": {
    "JD_type": "pass",
    "about_company": {
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        "last_5_words": "to excel in your career, we are the place for you."
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      "word_count": 116
    },
    "archetype_override_applied": true,
    "archetype_override_matched_skills": [
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      "Analytics",
      "Machine Learning",
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      "Location",
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    "certifications": [],
    "company_name": "Damco",
    "ctc": null,
    "domain": {
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        "country": "India",
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        "work_mode": "null"
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    ],
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        "source_marker": {
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        "word_count": 218
      }
    ],
    "urls": []
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  "rejected": false,
  "rejection_reason": null,
  "run_id": "509084e3-a67d-4ea3-9893-2679a53c2983",
  "stage3_signals": {
    "alias_found": false,
    "alias_match_roles": [],
    "kra_match_roles": [
      {
        "display_name": "Data Engineer",
        "kra_matches": [
          {
            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
            "sentence": "Ensure the delivery of high-quality, scalable, and reliable data solutions that meet client expectations.",
            "similarity": 0.5585
          },
          {
            "kra_text": "Designs dimensional models, star schemas, data vault structures, and curated data mart tables to support BI tools and self-service analytics consumption.",
            "sentence": "Drive the development and implementation of business intelligence strategies that support business goals and provide competitive advantages.",
            "similarity": 0.554
          },
          {
            "kra_text": "Works with data analysts, data scientists, and business stakeholders to define data models, ingestion schedules, and data delivery requirements.",
            "sentence": "Oversee the design and execution of advanced analytics projects, including predictive modeling, machine learning algorithms, and data visualization initiatives.",
            "similarity": 0.5529
          }
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        "role_id": 2,
        "score": 0.5551,
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        "total_count": null
      },
      {
        "display_name": "DevOps Engineer",
        "kra_matches": [
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            "similarity": 0.5634
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            "similarity": 0.5074
          },
          {
            "kra_text": "Monitors CI/CD pipeline reliability, identifies bottlenecks in delivery workflows, and improves deployment frequency, lead time, and failure recovery rate.",
            "sentence": "Ensure the delivery of high-quality, scalable, and reliable data solutions that meet client expectations.",
            "similarity": 0.4555
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 10,
        "score": 0.5088,
        "slug": "devops-engineer",
        "total_count": null
      },
      {
        "display_name": "Flutter Developer",
        "kra_matches": [
          {
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            "sentence": "Collaborate with cross-functional teams, including sales, marketing, and product development, to identify and capitalize on growth opportunities.",
            "similarity": 0.618
          },
          {
            "kra_text": "collaborate with design, product, and backend teams",
            "sentence": "Foster a culture of continuous improvement and innovation within the teams, encouraging the adoption of new technologies and methodologies.",
            "similarity": 0.4375
          },
          {
            "kra_text": "collaborate with design, product, and backend teams",
            "sentence": "Lead and manage the Data Engineering, AI, and Visualization teams, ensuring high performance and alignment with company objectives.",
            "similarity": 0.4369
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 74,
        "score": 0.4974,
        "slug": "flutter-developer",
        "total_count": null
      },
      {
        "display_name": "Engineering Manager",
        "kra_matches": [
          {
            "kra_text": "coach performance and growth",
            "sentence": "Mentor and develop team members, providing guidance and support to foster career growth and skill development.",
            "similarity": 0.5613
          },
          {
            "kra_text": "facilitate technical and delivery decisions",
            "sentence": "Ensure the delivery of high-quality, scalable, and reliable data solutions that meet client expectations.",
            "similarity": 0.458
          },
          {
            "kra_text": "Set team goals and delivery plans",
            "sentence": "Collaborate with cross-functional teams, including sales, marketing, and product development, to identify and capitalize on growth opportunities.",
            "similarity": 0.4446
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 121,
        "score": 0.4879,
        "slug": "engineering-manager",
        "total_count": null
      },
      {
        "display_name": "ML Engineer",
        "kra_matches": [
          {
            "kra_text": "Monitors production model behavior for data drift, concept drift, and prediction performance degradation using monitoring dashboards and alerting.",
            "sentence": "Monitor industry trends and advancements in business intelligence, AI, and data engineering to keep the company at the forefront of technology.",
            "similarity": 0.4774
          },
          {
            "kra_text": "Prepares, cleans, and transforms training datasets, manages feature stores, and builds feature engineering pipelines for model training.",
            "sentence": "Lead and manage the Data Engineering, AI, and Visualization teams, ensuring high performance and alignment with company objectives.",
            "similarity": 0.4689
          },
          {
            "kra_text": "Designs end-to-end ML training pipelines and model inference workflows using TensorFlow, PyTorch, or scikit-learn on cloud ML platforms.",
            "sentence": "Oversee the design and execution of advanced analytics projects, including predictive modeling, machine learning algorithms, and data visualization initiatives.",
            "similarity": 0.4647
          }
        ],
        "matched_count": null,
        "matched_skills": null,
        "role_id": 3,
        "score": 0.4703,
        "slug": "ml-engineer",
        "total_count": null
      }
    ],
    "skill_match_roles": [
      {
        "display_name": "ML Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Machine Learning"
        ],
        "role_id": 3,
        "score": 0.1667,
        "slug": "ml-engineer",
        "total_count": 6
      },
      {
        "display_name": "AI Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Machine Learning"
        ],
        "role_id": 13,
        "score": 0.1667,
        "slug": "ai-engineer",
        "total_count": 6
      },
      {
        "display_name": "MLOps Engineer",
        "kra_matches": null,
        "matched_count": 1,
        "matched_skills": [
          "Machine Learning"
        ],
        "role_id": 16,
        "score": 0.1667,
        "slug": "ml-ops-engineer",
        "total_count": 6
      }
    ]
  },
  "stage4_decision": {
    "alias_collision_detected": false,
    "case": "DOMAIN",
    "chosen_role": {
      "display_name": "Data Engineer",
      "kra_matches": null,
      "matched_count": null,
      "matched_skills": null,
      "role_id": 2,
      "score": 0.89,
      "slug": "data-engineer",
      "total_count": null
    },
    "confidence": 0.89,
    "is_new_role": false,
    "llm2_fired": false,
    "llm2_reasoning": null,
    "matched_dimensions": [
      "Data Team Leadership",
      "Business Intelligence Strategy",
      "Cross-functional Collaboration",
      "Advanced Analytics Delivery",
      "Client Solutioning",
      "Scalable Data Solutions",
      "Technology Innovation Monitoring",
      "Operational Management"
    ],
    "matched_kras": [
      "Lead and manage the Data Engineering, AI, and Visualization teams",
      "Drive the development and implementation of business intelligence strategies",
      "Collaborate with cross-functional teams",
      "Develop and maintain strong relationships with key clients",
      "Ensure the delivery of high-quality, scalable, and reliable data solutions",
      "Oversee the design and execution of advanced analytics projects",
      "Monitor industry trends and advancements",
      "Manage budgets, resource allocation, and project timelines",
      "Mentor and develop team members"
    ],
    "matched_skills": [
      "Data Engineering",
      "AI",
      "Visualization",
      "business intelligence",
      "predictive modeling",
      "machine learning algorithms",
      "data visualization",
      "resource allocation",
      "budget",
      "project timelines"
    ],
    "new_role_display_name": null,
    "new_role_slug": null,
    "queued": false,
    "reasoning": "Domain=Data Engineering \u0026 Analytics; The role is primarily a senior leadership position overseeing data engineering and analytics delivery, with responsibilities closest to a Data Engineer leadership scope rather than a hands-on BI developer or analyst role.",
    "sub_role": null
  },
  "stage5_updates": {
    "centroid_n_after": 276,
    "centroid_updated": true,
    "collision_log_id": null,
    "new_kra_attached": null,
    "new_skills_attached": [
      {
        "is_primary": true,
        "queue_id": 13573,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Engineering",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13574,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Data Visualization",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13575,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Business Intelligence",
        "status": "pending"
      },
      {
        "is_primary": true,
        "queue_id": 13576,
        "role_display_name": "Data Engineer",
        "role_slug": "data-engineer",
        "skill_name": "Predictive Modeling",
        "status": "pending"
      }
    ],
    "queue_entry_id": null,
    "v3_pipeline_triggered": false,
    "v3_role_slug": null,
    "v3_run_id": null
  }
}
API 2 — extract-details
{
  "alias_matches": [
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 1990,
      "existing_alias_text": "AI",
      "input_term": "AI",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "AI",
        "id": 1347,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "ai",
        "sub_category_id": 1020,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    },
    {
      "alias_persist_skipped_reason": "alias_text already exists for this canonical skill",
      "alias_persisted": false,
      "existing_alias_id": 2015,
      "existing_alias_text": "Machine Learning",
      "input_term": "Machine Learning",
      "matched_canonical": {
        "category_id": 2,
        "display_name": "Machine Learning",
        "id": 1356,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "machine-learning",
        "sub_category_id": 1024,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "matched_via": "alias"
    }
  ],
  "candidate_roles": [
    {
      "display_name": "AI Engineer",
      "id": 13,
      "rationale": null,
      "role_archetype": null,
      "slug": "ai-engineer",
      "source": "db"
    },
    {
      "display_name": "ML Engineer",
      "id": 3,
      "rationale": null,
      "role_archetype": null,
      "slug": "ml-engineer",
      "source": "db"
    },
    {
      "display_name": "MLOps Engineer",
      "id": 16,
      "rationale": null,
      "role_archetype": null,
      "slug": "ml-ops-engineer",
      "source": "db"
    }
  ],
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The role is primarily a senior leadership position overseeing data engineering and analytics delivery, with responsibilities closest to a Data Engineer leadership scope rather than a hands-on BI developer or analyst role.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "dimensions": [
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "AI",
      "llm_role": null,
      "roles_from_db": []
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "AI Governance and Model Security",
        "id": 50,
        "rationale": "Controls and documentation used to make models safer, auditable, and compliant. ML engineers use this to manage model risk, supply chain integrity, and governance requirements.",
        "slug": "ai-governance-and-model-security",
        "source": "db"
      },
      "input_skill": "Machine Learning",
      "llm_role": null,
      "roles_from_db": [
        {
          "display_name": "AI Engineer",
          "id": 13,
          "rationale": null,
          "role_archetype": null,
          "slug": "ai-engineer",
          "source": "db"
        },
        {
          "display_name": "ML Engineer",
          "id": 3,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-engineer",
          "source": "db"
        },
        {
          "display_name": "MLOps Engineer",
          "id": 16,
          "rationale": null,
          "role_archetype": null,
          "slug": "ml-ops-engineer",
          "source": "db"
        }
      ]
    },
    {
      "dimension": {
        "difficulty_hint": "well_known",
        "display_name": "React Frontend Development",
        "id": 96,
        "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
        "slug": "d_init_01",
        "source": "db"
      },
      "input_skill": "Machine Learning",
      "llm_role": null,
      "roles_from_db": []
    }
  ],
  "input_final_skills": [
    "Data Engineering",
    "AI",
    "Data Visualization",
    "Business Intelligence",
    "Predictive Modeling",
    "Machine Learning"
  ],
  "input_llm_skills": [
    "Data Engineering",
    "AI",
    "Data Visualization",
    "Business Intelligence",
    "Predictive Modeling",
    "Machine Learning"
  ],
  "new_aliases_persisted": 0,
  "run_id": "509084e3-a67d-4ea3-9893-2679a53c2983",
  "skills_detail": [
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Data Engineering",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "data-engineering",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "AI",
          "alias_type": "CANONICAL",
          "id": 1990,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 2,
        "display_name": "AI",
        "id": 1347,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "ai",
        "sub_category_id": 1020,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "AI",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "AI",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Data Visualization",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "data-visualization",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Business Intelligence",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "PRACTICE",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "business-intelligence",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [],
      "canonical": null,
      "dimensions": [],
      "input_skill": "Predictive Modeling",
      "matched_via": null,
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": {
        "derived": {
          "category": "Data Engineering Tools",
          "skill_nature": "CONCEPT",
          "sub_category": "general",
          "typical_lifespan": "MULTI_YEAR",
          "version_strategy": "UNVERSIONED",
          "volatility": "MEDIUM"
        },
        "enrichment": null,
        "keep_log": [],
        "locked_dimensions": [],
        "merge_log": [],
        "placed": null,
        "relationships": null,
        "skill_id": "predictive-modeling",
        "split_log": [],
        "typed": null,
        "warnings": []
      },
      "source_tag": "llm",
      "was_in_llm_skills": true
    },
    {
      "aliases_in_db": [
        {
          "alias_text": "Machine Learning",
          "alias_type": "CANONICAL",
          "id": 2015,
          "is_primary": false,
          "match_strategy": "CASE_INSENSITIVE"
        }
      ],
      "canonical": {
        "category_id": 2,
        "display_name": "Machine Learning",
        "id": 1356,
        "is_also_category": false,
        "is_extractable": true,
        "skill_nature": "CONCEPT",
        "slug": "machine-learning",
        "sub_category_id": 1024,
        "typical_lifespan": "EVERGREEN",
        "volatility": "STABLE"
      },
      "dimensions": [
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "AI Governance and Model Security",
            "id": 50,
            "rationale": "Controls and documentation used to make models safer, auditable, and compliant. ML engineers use this to manage model risk, supply chain integrity, and governance requirements.",
            "slug": "ai-governance-and-model-security",
            "source": "db"
          },
          "input_skill": "Machine Learning",
          "llm_role": null,
          "roles_from_db": [
            {
              "display_name": "AI Engineer",
              "id": 13,
              "rationale": null,
              "role_archetype": null,
              "slug": "ai-engineer",
              "source": "db"
            },
            {
              "display_name": "ML Engineer",
              "id": 3,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-engineer",
              "source": "db"
            },
            {
              "display_name": "MLOps Engineer",
              "id": 16,
              "rationale": null,
              "role_archetype": null,
              "slug": "ml-ops-engineer",
              "source": "db"
            }
          ]
        },
        {
          "dimension": {
            "difficulty_hint": "well_known",
            "display_name": "React Frontend Development",
            "id": 96,
            "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
            "slug": "d_init_01",
            "source": "db"
          },
          "input_skill": "Machine Learning",
          "llm_role": null,
          "roles_from_db": []
        }
      ],
      "input_skill": "Machine Learning",
      "matched_via": "alias",
      "new_alias_persisted": false,
      "new_alias_text": null,
      "new_skill_meta": null,
      "source_tag": "db",
      "was_in_llm_skills": true
    }
  ],
  "unmatched_skills": [
    "Data Engineering",
    "Data Visualization",
    "Business Intelligence",
    "Predictive Modeling"
  ]
}
API 3 — final-role-output
{
  "chosen_role": {
    "display_name": "Data Engineer",
    "id": 2,
    "rationale": "Domain=Data Engineering \u0026 Analytics; The role is primarily a senior leadership position overseeing data engineering and analytics delivery, with responsibilities closest to a Data Engineer leadership scope rather than a hands-on BI developer or analyst role.",
    "role_archetype": null,
    "slug": "data-engineer",
    "source": "db"
  },
  "chosen_role_resolution": "in_db",
  "final_input_skills": [
    {
      "skill": "Data Engineering",
      "tag": "new"
    },
    {
      "skill": "AI",
      "tag": "in_db"
    },
    {
      "skill": "Data Visualization",
      "tag": "new"
    },
    {
      "skill": "Business Intelligence",
      "tag": "new"
    },
    {
      "skill": "Predictive Modeling",
      "tag": "new"
    },
    {
      "skill": "Machine Learning",
      "tag": "in_db"
    }
  ],
  "llm_cost_api1_usd": null,
  "llm_cost_api2_usd": null,
  "llm_cost_api3_usd": null,
  "llm_cost_total_usd": null,
  "persistence": {
    "items": [
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "AI",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1347,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "AI Governance and Model Security",
          "id": 50,
          "rationale": "Controls and documentation used to make models safer, auditable, and compliant. ML engineers use this to manage model risk, supply chain integrity, and governance requirements.",
          "slug": "ai-governance-and-model-security",
          "source": "db"
        },
        "dimension_id": 50,
        "input_skill": "Machine Learning",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [
          {
            "display_name": "AI Engineer",
            "id": 13,
            "rationale": null,
            "role_archetype": null,
            "slug": "ai-engineer",
            "source": "db"
          },
          {
            "display_name": "ML Engineer",
            "id": 3,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-engineer",
            "source": "db"
          },
          {
            "display_name": "MLOps Engineer",
            "id": 16,
            "rationale": null,
            "role_archetype": null,
            "slug": "ml-ops-engineer",
            "source": "db"
          }
        ],
        "skill_dimension_saved": true,
        "skill_id": 1356,
        "skill_tag": "in_db",
        "skipped_reason": null
      },
      {
        "chosen_role_id": 2,
        "dimension": {
          "difficulty_hint": "well_known",
          "display_name": "React Frontend Development",
          "id": 96,
          "rationale": "Building interactive web user interfaces with React.js, including component composition, state management, hooks, and rendering patterns. React.js belongs here because it is a core library for client-side UI development in modern web applications.",
          "slug": "d_init_01",
          "source": "db"
        },
        "dimension_id": 96,
        "input_skill": "Machine Learning",
        "llm_role": null,
        "matched_chosen_role": false,
        "outcome_line": "Existing dimension (library) \u00b7 Role\u2194dimension skipped (dimension not under chosen role)",
        "role_dimension_saved": false,
        "roles_from_db": [],
        "skill_dimension_saved": true,
        "skill_id": 1356,
        "skill_tag": "in_db",
        "skipped_reason": null
      }
    ],
    "new_skills_created": 0,
    "role_dimension_saved": 0,
    "skill_dimension_saved": 0,
    "skipped": 0
  },
  "planner_output": null,
  "run_id": "509084e3-a67d-4ea3-9893-2679a53c2983"
}

LLM Calls

Every model call made for this run, in pipeline order. Click a card to see the model's response.

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