Associate Director/Senior Manager, Data Science (Statistical Programming)

About this role

Alumis Inc. is a precision medicines company with the mission to transform the lives of patients with autoimmune diseases. Even with treatment innovations of the last two decades, many patients with immunologic conditions continue to suffer - our goal is to fundamentally change the outcomes for these patients.

Alumis Inc is a precision medicines company with the mission to transform the lives of patients with autoimmune diseases. Even with treatment innovations of the last two decades, many patients with immunologic conditions continue to suffer – our goal is to fundamentally change the outcomes for these patients.

We are seeking a Data Science leader within Statistical Programming to advance analytical insights across clinical development while supporting high-quality, submission-ready deliverables. You will employ modern data science methods and tools such as machine learning, generative AI, and agentic AI to strengthen statistical programming and elevate analytical insight generation. You will contribute to both clinical data science (enhancing analyses, insights, and submissions) and operational/enterprise analytics (improving efficiency, scalability, and decision-making across Biometrics).

Depending on level, this individual will operate as a hands-on study/program contributor (Senior Manager) or a program-level leader influencing strategy and cross-functional execution (Associate Director).

Essential Responsibilities

Clinical Evidence Generation, Analytical Insights, and Regulatory Engagement

• Develop and deliver data science analyses to support clinical development, regulatory submissions, publications, and exploratory analyses.

• Partner with Biostatistics to support innovative analyses (e.g., simulations, external controls, RWE integration, predictive analytics using ML/GenAI models).

• Ensure alignment between exploratory analytics and CDISC-based submission deliverables; maintain documentation for inspection readiness.

• Support analysis of emerging data types (e.g., biomarkers, digital endpoints, real-world data, text, imaging), ensuring interpretability and quality.

• Contribute to responses to regulatory queries and preparation of submission materials involving advanced analytics.

Technical Execution & Innovation

• Develop and maintain analysis workflows using SAS and/or open-source tools (R/Python), balancing innovation with compliance.

• Build reusable tools, macros, templates and pipelines to improve efficiency, reproducibility, and scalability.

• Contribute to reproducible analysis pipelines (e.g., version control, data engineering and pipeline automation).