Biomarker Data ScientistBayer CropScience Limited • Whippany, New Jersey, United States

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Biomarker Data Scientist

Bayer CropScience Limited

Whippany, New Jersey, United States

Whippany, New Jersey, United States

About

Biomarker Data Scientist As Biomarker Data Scientist within the Digital Health & Real World Sciences team, you are an integral part of the DS&AI organization within R&D. You develop innovative solutions to enhance the analysis of large datasets and diverse data types, such as clinical trial data, biomarkers, digital markers, and real‑world data (RWD). Your statistical expertise will contribute to cross‑functional teams and ensure the appropriate and efficient use of statistical planning and analysis methods during clinical development of Bayer products. You will help bridge the gap between machine learning and clinical statistics by integrating machine learning techniques into existing clinical workflows while also pursuing novel approaches to modeling varied responses across patient subgroups. Responsibilities Perform advanced statistical analyses for clinical and biomarker studies, including causal inference, Bayesian methods, time‑series analysis, and high‑dimensional data analysis. Execute exploratory and confirmatory biomarker analyses across clinical trial data, omics data, and real‑world data sources. Evaluate and prototype advanced analytical methods through literature review, applied use cases, and method validation. Support statistical evaluation strategies and analysis plans (e.g., SAPs, BEPs) for assigned studies and contribute statistical input to study protocols, including sample size calculations and methodological justification. Develop and implement standard processes for the analysis of routine wet and digital biomarker assessments and automate insight generation for the production of statistical reports, presentations, and publications. Develop and maintain analytical code, pipelines, and tools to support study execution. Create and contribute to training materials on statistical and machine learning methods for clinical data analysis. Work independently on routine and complex quantitative questions and tasks. Act as go‑to person with accountability for the incorporation of advanced statistical concepts into digital statistical solutions and develop statistics application prototypes, including requirements. Collaborate closely with scientists from various disciplines across DS&AI and R&D, external software companies, and academic partners as needed. Oversee and ensure accurate and timely delivery of quantitative work outsourced to external providers. Required Qualifications MSc, PhD degree in statistics, biostatistics, computer science, bioinformatics, or closely related fields with several years of experience in the pharmaceutical industry. Strong programming skills in R and/or Python for data preprocessing, data analysis, statistical modeling, and machine learning, and solid SQL skills for data querying and manipulation. Experience with large and complex datasets, including data extraction, cleaning, transformation, and feature engineering in a reproducible way; experience collaborating with data engineers on data pipelines is a plus. Experience with clinical data domain standards such as CDISC and a solid understanding of their application in the context of randomized controlled trials (RCTs) and study designs. Familiarity with real‑world data (RWD) sources and methodologies, including the ability to integrate and analyze RWD for insights and evidence generation in life sciences. Good understanding of software design principles and experience building reproducible analysis workflows and model pipelines. Familiarity with modern data and ML tooling and ability to collaborate effectively with data and ML engineers. Comfortable using AI‑assisted coding tools to accelerate development and exploration while retaining responsibility for code quality and analytical rigor. Experience exposing models or analyses via simple APIs or integrating with existing applications is an advantage, but not the primary focus. Experience developing and validating GxP‑compliant analytical code and software, contributing to protocols, statistical analysis plans, and other regulatory‑relevant documents. Ability to work effectively independently and cross‑functionally, depending on project requirements. Outstanding problem‑solving ability to resolve challenging scientific tasks. Strong interpersonal skills and excellent written and verbal communication. Preferred Qualifications Minimum of 5 years practical experience as a data scientist with at least two years spent in pharma, biotech or similar sector. Salary & Benefits Salary range: $104,480.00 – $156,720.00. Additional compensation may include bonus or commission if relevant. Benefits include health care, vision, dental, retirement, PTO, sick leave, etc. Location United States – Cambridge, MA or Whippany, NJ. EEO Statement Bayer is an Equal Opportunity Employer / Disabled / Veterans. Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodations. Bayer is an E-Verify Employer. This posting will be available for application until at least 06/30/2026.
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Whippany, New Jersey, United States

Languages

English

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