Associate Director, Real-World Analytics Programming

Responsibilities

• Serves as the lead statistical programmer for assigned real-world studies and manage programming activities from study kickoff through final delivery.
• Leads programming deliverables from study initiation through final report, including analysis dataset specifications, TLF shells, validation plans, programming documentation, and final study outputs.
• Reviews and understand study-specific documents including protocols, SAPs, analysis specifications, and study concept documents to ensure accurate implementation of study requirements.
• Translates study designs and analytic specifications into efficient, scalable, and reproducible programming solutions.
• Independently develops, validates, and maintains SAS, SQL, R, Python, and other programming solutions for cohort construction, endpoint derivation, analysis dataset creation, and study deliverables.
• Generates and quality-control analysis datasets, tables, listings, and figures (TLFs) in accordance with study protocols, SAPs, analysis specifications, and internal standards.
• Supports a broad range of HEOR/RWE studies, including treatment pattern analyses, burden of illness studies, comparative effectiveness and safety studies, natural history studies, and external control arm analyses.
• Implements and validate analytic methods specified in study protocols and SAPs, including survival analyses, propensity score approaches, confounding adjustment methods, and sensitivity analyses.
• Works with multiple oncology-focused real-world data assets, including claims, electronic health records (EHR), genomic testing databases, and linked clinical-genomic datasets.
• Assesses data quality, completeness, and fitness-for-purpose and provide recommendations regarding data availability and implementation feasibility.
• Independently performs quality control and validation activities for programming code, analysis datasets, and study outputs.
• Develops and maintains technical documentation, programming specifications, reusable code, macros, and reproducible analytic workflows for assigned studies.
• Collaborates closely with HEOR/RWE scientists, Data Scientists, and Biostatisticians to ensure accurate implementation of study methodologies and successful delivery of study objectives.
• Communicates programming assumptions, implementation decisions, timelines, and risks to study teams and stakeholders.
• Contributes to real-world programming standards, quality frameworks, and best practices.
• Provides technical guidance to junior programmers as appropriate.
• Stays current with evolving industry best practices, technologies, and regulatory expectations related to oncology real-world data and evidence generation.

Required Skills, Experience and Education

• BS/MS degree in Statistics, Biostatistics, Computer Science, Data Science, Epidemiology, Mathematics, or a related quantitative discipline.
• 8+ years of statistical programming experience in pharmaceutical, biotechnology, CRO, healthcare research, or related settings for Senior-level candidates.
• Demonstrated experience independently leading programming activities for observational research, HEOR, epidemiology, or real-world evidence studies.
• Strong SAS or R programming experience required, including experience developing analysis datasets and study deliverables from complex healthcare data sources.
• Experience with SQL required and working knowledge of R or other programming language for data manipulation, analytics support, and quality control activities preferred.
• Experience developing analysis datasets, tables, listings, and figures (TLFs) from complex healthcare or real-world data sources.
• Experience working with large healthcare databases, including claims, EHR, genomic, registry, or linked clinical-genomic datasets.
• Strong understanding of observational research workflows and implementation of study specifications.
• Demonstrated ability to manage multiple projects simultaneously while meeting timelines and quality expectations.
• Excellent written and verbal communication skills.
• Strong analytical, problem-solving, and organizational skills with exceptional attention to detail.
• Thrives in a collaborative team environment and is motivated to drive high-quality technical execution and continuous process improvement.

Preferred Skills

• Oncology drug development or oncology real-world evidence experience.
• Experience working with major oncology or healthcare real-world data assets, such as Flatiron Health, ConcertAI, COTA, Tempus, Guardant, Merative MarketScan, Komodo, Optum, TriNetX, or similar datasets.
• Experience supporting HTA, market access, indirect treatment comparison (ITC), external control arm, or regulatory-grade real-world evidence studies.
• Experience developing reusable programming frameworks, standardized macros, and validation tools.
• Experience with Git, version control systems, and reproducible analytics workflows.
• Experience working in a fast-paced and growing biotechnology organization.