Associate Director - AI/ML Data Scientist

Scorpion Therapeutics; Indianapolis (IN); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Bonus eligibility

Comprehensive benefits

Job summary

Lilly is seeking a Senior Data Scientist to develop advanced analytics, ML, and AI for the People Intelligence platform. You will design and operationalize models for workforce use cases and translate findings for HR leaders and product owners.

Responsibilities include governance, bias/privacy safeguards, and reusable pipelines, with integration to Fabric Data Agents, Power BI, and enterprise experiences.

Qualifications

• BS in data science/statistics/ML or related.
• 4+ years Python proficiency; develop/validate/operationalize predictive models.
• 5+ years statistical inference, experimental design, model evaluation, data-quality assessment.

Responsibilities

• Design, validate, and operationalize statistical/ML/AI models for workforce use cases.
• Build predictive capabilities for attrition, talent risk, hiring, mobility, and planning.
• Develop AI-enabled analytics and reusable AI workflows.
• Create semantic models and integrate into Fabric, Power BI, and Enterprise experiences.
• Establish governance, monitoring, explainability, and bias/privacy safeguards.

Skills

Python programming

Predictive modeling

Statistical inference

Experimental design

Model evaluation

Data-quality assessment

Education

BS in data science or statistics or ML

Tools

Microsoft Fabric

Spark

Power BI

Azure AI

Fabric Data Agents

Job description

Position Overview:

Senior Data Scientist to develop advanced analytics, machine learning, and AI that convert governed workforce data into actionable intelligence for Lilly's People Intelligence platform.

What You'll Be Doing:

• - Design, validate, and operationalize statistical/ML/AI models for workforce use cases.
• - Build predictive capabilities for attrition, talent risk, employee experience, hiring, mobility, skills, org health, and workforce planning.
• - Use regression/classification/clustering/forecasting, causal inference, NLP, anomaly detection, and scenario modeling.
• - Develop AI-enabled analytics (risk signals, probabilistic guidance, recommended follow-ups); create reusable AI skills/workflows/prompts.
• - Build semantic models and make models AI-ready for Fabric; integrate into Fabric Data Agents, Power BI, MCP, and approved enterprise experiences.
• - Establish governance/measurement: validation, monitoring, explainability, retraining/retirement; define performance thresholds; manage bias/fairness/privacy/unintended consequences; ensure reproducible methods.
• - Advise HR leaders and product owners; translate findings into decision-oriented language; convert analyses into reusable models/metrics/products; coach others.

Key Deliverables:

Predictive/causal workforce models; governed semantic data models; generative AI text analytics (sentiment/theme extraction); model accuracy/testing frameworks; monitoring/governance standards; reusable ML pipelines/feature stores; scenario planning/workforce simulations; explainable AI outputs.

Basic Qualifications:

• - BS in data science/statistics/ML or related.
• - 4+ years Python proficiency; develop/validate/operationalize predictive models.
• - 5+ years statistical inference, experimental design, model evaluation, data-quality assessment.

Strongly Preferred:

• - Advanced degree (quantitative/behavioral) and/or AI certification.
• - Large complex longitudinal datasets; executive communication.
• - Workforce/people analytics; independent judgment with sensitive employee data.
• - Microsoft Fabric/Spark/Power BI/Azure AI/Fabric Data Agents.
• - NLP, generative AI/RAG, causal inference, organizational network analysis, workforce forecasting; responsible AI/privacy/governance familiarity.

Additional Information (Benefits):

• - Eligible for company bonus (full-time equivalent).
• - Comprehensive benefits: 401(k), pension, vacation, medical/dental/vision/prescription, flexible benefits (e.g., FSA), life insurance, time off/leave of absence, well-being benefits (e.g., EAP, fitness, employee clubs/activities).