AI & Data Science Lead
First seen by Alion on Sep 24, 2026.
Role: AI & Data Science Lead (Pharma/Life Sciences)
Experience: 7+ years
Location: Bangalore, WFO (Hybrid)
Must Have Skills:
- 7+ years in Data Science & AI Leadership: Extensive experience in Advanced Analytics, specifically within Pharma or Life Sciences, showing a clear evolution from classical DS to AI-driven solutions.
- Expertise in Pharma Data Ecosystems: Deep hands-on experience with Patient-level data (Claims, EHR/EMR, Rx, Longitudinal Cohorts, HCP and Patient Master) and an understanding of data sparsity/biases.
- Advanced Modeling & Causal Inference: Mastery of supervised/unsupervised techniques (Regression, Clustering, Segmentation, Propensity) with a strong focus on Causal Inference to distinguish correlation from impact in commercial/medical decisions.
- GenAI & LLM Architecture: Proven experience designing and implementing GenAI workflows (RAG, Agentic Frameworks, Prompt Engineering) for insight extraction, summarization, or decision-support tools.
- Strategic Roadmap & Stakeholder Management: Ability to translate complex HCP/Patient business questions into structured AI Roadmaps and high-impact visualizations (Power BI / Tableau) for senior leadership.
- End-to-End Product Lifecycle: Experience leading an AI/Analytics product from problem discovery and MVP design through to production rollout and MLOps (monitoring for model drift and accuracy).
- Technical Stack: Advanced proficiency in Python and SQL; experience building scalable solutions on Cloud platforms (Databricks, Snowflake, AWS, or Azure).
Good to Have:
- Therapeutic Area Depth: Prior work in CV/Metabolic, Oncology, Immunology, or Rare Diseases, including patient journey mapping and payer/access dynamics.
- Commercial Strategy: Experience using analogue launches to inform Field-force design, Launch strategy, and Patient-funnel optimization.
- AI Governance: Familiarity with Data Privacy (HIPAA/GDPR) and ethical AI guardrails within a regulated Pharma environment.
- Advanced Analytics: Exposure to Uplift modeling and Reinforcement Learning for personalized engagement strategies.
Soft Skills:
- Strategic Business Acumen: Can bridge the gap between technical AI capabilities and Senior Commercial/Medical objectives.
- Exceptional Storytelling: Ability to communicate complex data narratives to non-technical stakeholders with clarity and persuasion.
- Ownership & Mentorship: High degree of accountability and the ability to guide junior DS talent through ambiguous, fast-paced launch environments.
Skills
Data Science, Analytics, Artificial Intelligence, Data Analytics, Machine Learning, Data Governance