> Markdown version of [/jobs/ext/2571780-associate-director-ai-ml-data-scientist](https://www.wearedevelopers.com/jobs/ext/2571780-associate-director-ai-ml-data-scientist). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Associate Director - AI/ML Data Scientist - **Company:** Eli Lilly and Company - **Location:** Indianapolis, IN, United States - **Experience:** Expert - **Salary:** $127,500.0 - $204,600.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Microsoft Azure, Network Analysis, Cluster Analysis, HR Analytics, Python (Programming Language), Machine Learning, Natural Language Processing, Power BI, Apache Spark, Model Validation, Generative AI, Microsoft Fabric, Data Analytics, Machine Learning Operations - **Published:** August 24, 2026 - **Apply:** https://www.biospace.com/logon?PipelinedPage=%2Fjob%2F3070526%2Fassociate-director-ai-ml-data-scientist%3FAction%3DContinueJobApplication%23application-form ## About the Role * Bachelors Degree in data science, statistics, machine learning or related field. * 4 years minimum Python proficiency and experience developing, validating, and operationalizing predictive models * 5 years of statistical inference, experimental design, model evaluation, and data-quality assessment experience. Additional Skills / Strongly Preferred * Advanced degree in a quantitative or behavioral field (eg Statistics, Data Science or related) * AI Certification highly desirable * Experience working with large, complex, longitudinal datasets, with strong executive-level communication skills * Ability to operate independently, influence without authority, and exercise strong judgment with sensitive employee-level data * Workforce or people analytics experience * Experience with Microsoft Fabric, Spark, Power BI, Azure AI, or Fabric Data Agents * Experience with NLP, generative AI, RAG, causal inference, organizational network analysis, or workforce forecasting * Familiarity with responsible AI, privacy, and employment-model governance standards ## Description We're looking for a Senior Data Scientist to lead the development of advanced analytics, machine learning, and AI capabilities that turn governed workforce data into actionable intelligence. In this role, you'll design predictive, probabilistic, and explanatory models that strengthen the accuracy and reliability of Lilly's People Intelligence platform - the enterprise capability that turns workforce data into decision-ready insight for HR leaders and the business. What You'll Be Doing Advanced Analytics & Data Science * Design, validate, and operationalize statistical, machine-learning, and AI models for workforce use cases * Develop predictive capabilities spanning attrition, talent risk, employee experience, hiring, mobility, skills, organizational health, and workforce planning * Apply regression, classification, clustering, forecasting, causal inference, NLP, anomaly detection, and scenario modeling as appropriate * Translate ambiguous workforce questions into clear analytical problems, hypotheses, methods, and measurable outcomes AI-Enabled People Intelligence * Develop analytical logic for directional insights, risk signals, probabilistic guidance, and recommended follow-up questions * Create and validate reusable AI skills, analytical workflows, prompts, and reasoning frameworks * Build semantic models and drive Fabric architecture to be AI ready * Evaluate the factual accuracy, analytical validity, consistency, and business usefulness of AI-generated responses * Integrate models into Fabric Data Agents, Power BI, MCP, and other approved enterprise experiences Measurement & Governance * Establish standards for validation, documentation, monitoring, explainability, retraining, and retirement * Define performance measures, confidence levels, thresholds, and evaluation frameworks * Identify bias, fairness, privacy, and unintended-consequence risks; partner with governance, privacy, legal, ER, and responsible-AI teams * Communicate assumptions, limitations, and uncertainty, and maintain reproducible analytical methods Consulting & Technical Leadership * Serve as a senior analytical advisor to HR leaders, HRBPs, Centers of Excellence, and product owners * Distinguish descriptive findings, correlations, predictions, and causal conclusions in decision-oriented language * Convert high-value analyses into reusable models, metrics, semantic-model enhancements, AI skills, or enterprise products * Coach analysts and technical team members in advanced analytical methods Key Deliverables * Predictive and causal workforce models - attrition/flight-risk forecasting, hiring-funnel and mobility prediction * Governed semantic data models - reusable, self-service-ready data models spanning workforce, survey, and talent domains * Generative AI-enabled employee-experience and text-analytics capabilities - sentiment/theme extraction from check-in notes, Pulse, and Leadership Compass verbatims * Model accuracy, testing, and response-evaluation frameworks - validation pipelines benchmarking model outputs before production release * Model-monitoring, model-governance, and responsible-AI standards - drift detection, bias/fairness checks, documented model lineage * Reusable ML pipelines, feature stores, and data-science assets - production-grade, shared across workforce use cases rather than rebuilt per project * Scenario-planning and workforce-simulation models - what-if modeling for merit, span-of-control, and org-design decisions * Explainable AI (XAI) outputs and responsible-use guidance - interpretable model outputs paired with documented guardrails for HR decision-making, * Independently leads complex, ambiguous, enterprise-level analytical initiatives * Establishes technical standards and influences People Intelligence strategy across workforce domains * Creates reusable capabilities, mentors others, and improves team analytical maturity * Influences senior stakeholders through credible evidence and clear recommendations * Balances innovation, governance, responsible use, and measurable business value Measures of Success Improved insight accuracy and usefulness across the People Intelligence platform; operationalized analytical capabilities; adoption in workforce decisions; model performance, stability, and explainability; reduced one-time analysis through reusable assets; demonstrated business outcomes; and compliance with privacy, responsible-AI, and analytical-governance standards. Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response. ## Related Videos - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [Beyond Dashboards: Fixing Text-to-SQL with Semantic RAG](https://www.wearedevelopers.com/videos/2036-beyond-dashboards-fixing-text-to-sql-with-semantic-rag) - [Beyond Gut Feelings: The Rise of Data-Driven HR](https://www.wearedevelopers.com/videos/1326-beyond-gut-feelings-the-rise-of-data-driven-hr) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [AI for decision-making in Tech Recruiting](https://www.wearedevelopers.com/videos/1074-ai-for-decision-making-in-tech-recruiting) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) ## Related Articles - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)