Director/Senior Director, Product - Applied Data Science
Leads the strategy and execution for scaling data science analyses into durable tools and capabilities for drug-asset acquisition and diligence. The role requires senior experience across data science or technical product, life sciences expertise, AI/ML fluency, and the ability to coordinate engineering and data science teams.
About the job
Responsibilities
- Own the strategy for scaling data science work for asset acquisition and diligence.
- Determine which one-off analyses have generalization potential and whether they should become landscape analyses or scaled tools.
- Set the roadmap and sequence work based on business impact while coordinating resourcing with functional leads.
- Direct a working team spanning Data Science and Engineering day to day.
- Partner strategically with Data Science and Business Development to translate scientific findings into a scalable roadmap.
- Guide technical approaches for statistical validity, pipeline design, and dataset evaluation at exhaustive scale.
- Identify opportunities for AI to improve asset acquisition and diligence, and communicate resourcing needs and business impact to stakeholders.
Requirements
- 7+ years of experience in data science, applied science, or technical product roles with progressively broader scope.
- Experience turning analytical work into a deployed capability.
- Experience in biotech, pharma, or a related life sciences industry, with understanding of the drug development lifecycle.
- Ability to evaluate what analytical work is worth scaling based on scientific and business impact.
- AI/ML fluency, including evaluating methods at scale and making build-versus-buy tooling decisions.
- Technical fluency in data science, engineering, statistical methods, architecture, and trade-offs.
- Experience directing or coordinating technical teams, including engineers and data scientists.
- Business fluency in diligence findings, asset valuation, and scientific risk.
- Comfort with ambiguity and autonomy.
Compensation and Benefits
- Total compensation range: $245,000 - $307,000.
- Compensation may include base salary, equity, comprehensive benefits, and generous perks.
- Hybrid work model requiring 3 days per week in the office.
Skills
Data Science, Machine Learning, Artificial Intelligence, Statistical Analysis, Causal Modeling, Data Pipelines, Dataset Evaluation, Drug Development, Asset Valuation, Data Engineering
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