Senior Quantitative Biomarker Scientist

About the role

Regeneron is advancing its pipeline portfolio using a data‑driven human translational approach. The Precision Medicine team is integrated with Discovery Research and Clinical Development to promote early adoption of biomarker strategy that guides clinical translation. The team collaborates with Clinical Sciences to develop clinical experimental sciences (CES) studies for generating testable, mechanistic hypotheses for each molecule, including scientific rationale for initial and new indications for proof‑of‑concept. Precision Medicine leads biomarker strategy and execution to achieve proof of mechanism/concept in early clinical trials and implements precision‑medicine strategies (patient stratification, selection) to support late‑stage programs and companion diagnostics. This role sits within Precision Medicine Quantitative Translational Sciences (PMQTS), the analytical arm of Precision Medicine.

Responsibilities

• Liaise with Precision Medicine Quantitative Translational Sciences to analyze biomarker data types across a range of Precision Medicine and biomarker studies.
• Provide computational and technical expertise on data cleaning and data visualization.
• Integrate complex datasets to perform statistical analysis on exploratory biomarker data and clinical endpoints.
• Use technical tools, language, or custom coding and systems analysis to clean data and select or create datasets for analysis.
• Understand and follow data quality concepts and best practices and tools.
• Identify data anomalies and work with data stewards in other units to perform root cause analysis on data quality issues.
• Assist in the preparation of scientific presentations, manuscripts, and reports, including the preparation of quality‑checked tables and graphs depicting research results.
• Effectively communicate analytical plans and timelines for multiple concurrent projects with study team members.
• Develop, benchmark, and implement new computational workflows as necessary.
• Maintain best coding and data cataloguing practices for business consistency and scientific reproducibility.

Requirements

PhD, or a Master’s degree with a minimum of 2 years of relevant work experience in one of the following or otherwise related quantitative fields: Computer Science, Computational Biology, Systems Biology, Quantitative Biology, Bioinformatics, Data Analytics, Statistics, Biostatistics, Mathematics, Applied Mathematics, Physics, or Chemistry.

Qualifications

• Experience with statistical modeling/regression, machine learning, and other relevant data‑blending abilities.
• Experience in at least one of the following scripting languages: R, Python, MATLAB (SQL, Spark, and C++ are a bonus).
• Experience working in a Linux and/or cloud environment, shell scripting, and notebook environments.
• Knowledge of structured data with the ability to perform data mapping for systems integration, data provisioning, and data consumption (strongly preferred).