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This role is based in the Real-World & Clinical Data Strategy (RWCDS) team which drives data excellence and analytics to power enhanced decision-making and evidence-generation within Roche Product Development. We develop and implement data strategies that unlock the value of clinical, operational, and real-world data to accelerate evidence generation, decision-making, and innovation across PD and beyond. By embedding FAIR principles, advancing data governance, and enabling data productization, RWCDS ensures that data is not only findable and usable, but also a driver of scientific rigor, regulatory readiness, and AI-powered transformation. Through deep partnerships with internal functions and external collaborators, we shape a future-ready data ecosystem that supports personalized healthcare and efficient drug development.
The Opportunity:
The Senior Data Strategy & Analytics Specialist plays a key role in designing and executing end-to-end data strategies and complex analytics that enable decision-making, asset strategy, and insight generation across therapeutic areas or molecule portfolios. Working under the Data Strategy & Analytics Lead, you act as a technical and strategic partner across cross-functional study teams - translating complex clinical and translational questions into robust analytical code, cohort extractions, and reproducible data workflows using multi-modal real-world data (RWD) and clinical trial data for secondary use (SUD).
As a senior specialist, you bring high technical autonomy, analytical rigor, and thought partnership. You drive best-in-class engineering and statistical principles, evaluate novel data assets, and mentor junior colleagues to elevate analytical standards across RWCDS.
The Senior Data Strategy & Analytics Specialist plays a key role in designing and executing end-to-end data strategies and complex analyses that enable decision-making, asset strategy, and insight generation across therapeutic areas or molecule portfolios. Working under the Data Strategy & Analytics Lead, you partner with cross-functional teams - translating scientific, clinical, and translational questions into robust analytical code, cohort extractions, and reproducible pipelines using multi-modal real-world data (RWD) and clinical trial assets for secondary use (SUD). You also contribute to the translation of scientific and business needs into analytical frameworks and data-driven solutions. This role demands advanced data science skills, strategic problem solving, and a commitment to elevating team standards through mentorship and technical leadership.
- You independently design and execute advanced cohort extractions, complex data transformations, and observational or exploratory analyses across diverse real-world (EHR, Claims, etc.), secondary clinical trial, and operational multi-modal data assets
- You lead the translation of complex scientific, translational, or business questions into robust cohort definitions, custom derived variables, and analysis-ready datasets
- You champion and enforce state-of-the-art coding standards, version control workflows, automated testing, and structured QC routines to guarantee fully reproducible, auditable analytical pipelines across the team
- You synthesize and communicate complex analytical outputs, cohort dynamics, and study findings to project teams and strategic decision-makers, delivering high-impact evidence to inform regulatory filings, medical decisions, and asset strategy
- You act as a strategic analytical partner to RWD Scientists and cross-functional study leads during early study framing, protocol development, and Integrated Evidence Plan (IEP) creation, advising on data feasibility, methodological rigor, and analytical strategy
- You establish reusable code libraries, analytical frameworks, and best-practice templates for the internal repository, actively mentoring junior team members to elevate technical execution
- You lead the evaluation and curation of fit-for-purpose real-world data sources, performing comprehensive data quality assessments, complex terminology mappings, and schema transformations for secondary data use
- You partner with study teams and central data engineering functions to drive requirement definition, define and validate complex derived variables (e.g., ADaM, ARDs), and architect clinical trial datamarts for secondary use
- You lead data harmonization and multi-modal integration efforts in partnership with data engineering and governance teams, applying healthcare common data models (OMOP, CDISC) and structured mappings across clinical trial and real-world assets
- You analyze complex data architectures, oversee data lineage documentation, and establish structured, compliant, and accessible data assets that support long-term data strategy, FAIR principles, and reusability
- You champion the safe adoption of modern AI coding tools and LLM assistants (e.g., Claude Code, Copilot) to accelerate analytical workflows, while establishing practices to safeguard scientific rigor and code quality
Who you are:
- You hold a Master’s or PhD in Quantitative Health Sciences (e.g., Biostatistics, Epidemiology), Data Science, or a closely related quantitative field
- You have 3+ years of experience working with structured healthcare data (real-world data, clinical trial data, or observational research) in a biopharmaceutical, academic research, or healthcare setting
- You possess advanced, demonstrated proficiency in R or Python, as well as strong working expertise in SQL for complex database querying and data wrangling
- You have working knowledge of metadata management, data standardization, or data mapping approaches
- You have the ability to translate research or operational needs into data requirements and workflows
- You have the capacity for independent thinking and ability to make decisions based upon sound principles
- You exhibit excellent strategic agility including problem-solving and critical thinking skills, and agility that extends beyond technical domain
- You demonstrate respect for cultural differences when interacting with colleagues in the global workplace
- You possess excellent verbal and written communication skills, specifically in the areas of presentation and writing, with the ability to explain complex technical concepts in clear language
Preferred Qualifications:
- Deep domain expertise or prior research experience in cardiovascular, renal, or metabolic (CVRM) disease areas, clinical endpoints, and disease-specific biomarkers
- Advanced understanding of observational study designs, confounding adjustment (propensity scores, matching), censoring, time-to-event or survival analysis, and descriptive biostatistics
- Practical experience building, transforming, or curating datasets using the OMOP Common Data Model or CDISC standards (SDTM, ADaM)
- Advanced knowledge of medical coding classifications and ontologies (e.g., ICD-9/10, SNOMED CT, RxNorm, LOINC, CPT, HCPCS) and their real-world mapping nuances
- Practical experience with Git/GitHub, CI/CD, containerized environments, and safe adoption of AI developer tooling (e.g., GitHub Copilot, Claude Code) to enhance productivity
- Demonstrated track record of acting as a consultative partner to clinical, observational, or translational research scientists in shaping study questions, evidence generation, and analytical strategy
Location
- This position is based in Boston, MA
- Relocation benefits are not available for this posting
The expected salary range for this position based on the primary location of Massachusetts is $107,400.00 - $199,400.00 USD Annual. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
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