Senior Scientist, Precision Medicine
Regeneron
Full-time
On-site
United States
Clinical Research and Development
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Role Summary
Senior Scientist, Precision Medicine at Regeneron. This is a statistical computational role in the Precision Medicine Quantitative Translational Sciences (PMQTS) analytic arm, focusing on clinical trial data management, data analysis, and development of tools for processing, analyzing, querying, visualizing, and cleaning biomarker data to drive Precision Medicine objectives.
Responsibilities
- Liaise with Precision Medicine Quantitative Translational Sciences to analyze biomarker data types across a range of 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 tools, language, or custom coding to clean data and create datasets for analysis.
- Understand and apply data quality concepts; identify data anomalies and work with data stewards to analyze root causes.
- Assist in preparing scientific presentations, manuscripts, and reports with quality-checked tables and graphs.
- Communicate analytical plans and timelines for multiple projects with study teams.
- Develop, benchmark, and implement new computational workflows as needed.
- Maintain best coding and data cataloguing practices for reproducibility.
Qualifications
- Required: PhD, or Master’s with minimum 2 years of relevant work experience in Computer Science, Computational Biology, Systems Biology, Quantitative Biology, Bioinformatics, Data Analytics, Statistics, Biostatistics, Mathematics, Applied Mathematics, Physics, or Chemistry.
- Preferred: Experience with statistical modeling/regression, machine learning, and data blending; proficiency in R, Python, or MATLAB; knowledge of SQL, Spark, C++; experience in Linux/cloud environments; familiarity with structured data mapping for system integration; working knowledge of clinical trials.
Skills
- Statistical modeling and machine learning
- Data cleaning and visualization
- Data integration across omics, EHR, wearables, imaging, and other biomarker data
- Programming in R, Python, MATLAB; SQL/Spark/C++ is a bonus
- Linux/cloud computing, shell scripting, notebook environments
- Data quality concepts and data governance
- Strong communication of analytical plans and results
Education
- PhD, or Master’s with minimum 2 years of relevant experience in the specified quantitative fields.