Senior Manager, RWE Biostats

Bristol Myers Squibb

. Advance Bristol Myers Squibb’s global drug development process through real-world data science and advanced analytics .

Posted 9/28/2026full-timeUnited StatesSenior💰 $164,110 - $228,701 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in real-world data science, statistical analysis, and predictive modeling, with a strong focus on oncology and clinical trial design. Proficient in utilizing advanced analytics and machine learning techniques to inform drug development and improve patient outcomes.

Highest-signal resume keywords

Ph.D. In A Relevant Quantitative FieldReal-World Data Science ExpertiseStatistical And Causal Inference MethodsProficiency In Python, R, And SQLExperience With Oncology RWD Platforms

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Statistical AnalysisCausal InferencePredictive ModelingData CleaningNLP-Based Feature ExtractionLongitudinal Data AnalysisBiomarker AnalysisSurvival AnalysisData VisualizationMachine Learning

Soft Skills

Problem-SolvingCollaborationCreative ThinkingCommunicationData Presentation

Tools & Technologies

AWSAzureDatabricksOMOP CDMFHIRICDSNOMEDRxNormNLPLLM

Industry Keywords

Real-World DataClinical TrialsOncologyDrug DevelopmentRegulatory Decision-MakingEHRClaimsRegistriesSynthetic Control AnalysesBiomarker-Driven Patient Stratification

Tech Stack

Tools & technologies

AWSAzureCloudPythonSQLSwitching

About the role

Key responsibilities & impact

Advance Bristol Myers Squibb’s global drug development process through real-world data science and advanced analytics
Build and maintain scalable pipelines for EHR, claims, registries, lab data, and linked datasets
Develop data quality frameworks and apply RWD standards and ontologies
Define patient identification, cohort selection, exposure, and outcome algorithms
Perform data cleaning, deduplication, record linkage, missing-data handling, and NLP-based feature extraction
Construct longitudinal patient-level datasets capturing treatment, disease progression, utilization, and outcomes
Build and validate oncology cohorts, biomarker subgroups, and treatment histories
Apply oncology RWD outcome methods and address immortal time bias, censoring, death ascertainment, and treatment switching
Support comparative effectiveness, external control arm, and synthetic control analyses
Apply statistical, epidemiological, survival, longitudinal, causal inference, and AI/ML methods
Develop, validate, and deploy predictive models for stratification, treatment response, disease progression, and prognostic factors
Use NLP and LLM approaches for RWD extraction, phenotyping, and evidence synthesis
Inform clinical trial design, feasibility, site selection, enrichment, estimands, dose selection, endpoints, and go/no-go decisions
Contribute to statistical analysis plans for RWD/RWE analyses
Analyze genomics, proteomics, imaging, flow cytometry, biomarker, and other multimodal clinical-trial data
Integrate, mine, visualize, and model disparate data types, including RWD and clinical-trial data
Collaborate with clinicians, translational scientists, biostatisticians, engineers, regulatory scientists, and IT professionals
Contribute through code reviews, technical mentorship, communication of results, resource coordination, and delivery of quality work

Requirements

What you’ll need

Ph.D. in a relevant quantitative field and 1+ years of academic/industry experience, or Master's Degree in a relevant quantitative field and 3+ years of industry experience
Deep, hands-on expertise in real-world data science across EHR, claims, and registries
Strong experience applying statistical and causal inference methods for observational RWD
Proficiency in Python, R, and SQL
Experience with AWS, Azure, Databricks, and distributed data environments
Experience with OMOP CDM, FHIR, ICD, SNOMED, and RxNorm
Experience developing and validating AI/ML predictive models on high-dimensional, longitudinal, and/or irregular real-world datasets
Strong experience in biomarker or multi-modal data analysis in pharma R&D
Familiarity with clinical trial design, drug development, and RWE regulatory and clinical decision-making
Ability to work independently and collaboratively on concurrent projects
Strong problem-solving, collaboration, rigorous and creative thinking
Excellent communication, data presentation, and visualization skills
Experience with NLP and/or LLM-based clinical text extraction, phenotyping, or evidence synthesis is highly preferred
Experience with causal ML and explainable AI applied to observational RWD is highly preferred
Experience with ECA or synthetic control analyses is highly preferred
Experience with genomics, proteomics, imaging, flow cytometry, or immunobiology datasets is highly preferred
Experience with survival analysis and time-to-event modeling is highly preferred
Hands-on experience with oncology RWD platforms and oncology-specific endpoints is highly preferred
Familiarity with biomarker-driven patient stratification and FDA oncology RWE guidance is preferred
Experience with federated data analysis, privacy-preserving analytics, or de-identification frameworks is a plus
Experience managing or integrating third-party RWD vendors, data providers, or analytics platforms is a plus
Experience with scalable compute, cloud-based data platforms, and parallelization

Benefits

Comp & perks

Comprehensive wellbeing support, retirement and financial protection benefits
Medical, dental, vision, life and disability insurance offerings
Flexible Time Off (FTO) for U.S.-based exempt employees
11 paid company holidays annually
160 hours of paid vacation annually for eligible new hires
3 optional holidays for eligible employees
Paid sick leave
Up to two paid volunteer days per year
Summer hours flexibility
Medical, personal, parental, caregiver, bereavement, and military leaves of absence
Annual Global Shutdown between Christmas Day and New Year's Day
Reasonable workplace accommodations/adjustments
Additional discretionary incentive cash and stock opportunities