Associate Director - AI/ML Data Scientist

About the role

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

Position Overview

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

Basic Qualifications

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

Additional Information

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.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is

$127,500 - $204,600

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

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