Associate Director, Real-World Analytics Programing

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Associate Director, Real-World Analytics Programing based in United States.

This is a senior statistical programming role supporting complex real-world analytics and evidence-generation studies in oncology. You will serve as a lead programmer, owning programming activities from study initiation through final deliverables and ensuring that analyses are accurate, reproducible, and aligned with study requirements. The role works closely with HEOR/RWE scientists, Data Scientists, Biostatisticians, and other cross-functional partners to translate study protocols and statistical analysis plans into high-quality outputs. You will work with large and complex healthcare data sources, including claims, electronic health records, genomic data, and linked clinical-genomic datasets. The position combines hands-on technical programming with study leadership, quality oversight, and methodological implementation. It offers the opportunity to contribute to impactful real-world evidence programs while helping advance programming standards, reusable workflows, and analytical best practices.

Accountabilities:

• Serve as the lead statistical programmer for assigned real-world analytics studies, independently managing programming activities from study kickoff through final study delivery and reporting.
• Lead programming deliverables across the study lifecycle, including analysis dataset specifications, TLF shells, validation plans, programming documentation, analysis datasets, and final study outputs.
• Review study protocols, statistical analysis plans, analysis specifications, and study concept documents to ensure programming solutions accurately reflect study objectives and methodological requirements.
• Translate study designs and analytical specifications into efficient, scalable, maintainable, and reproducible programming solutions using SAS, SQL, R, Python, and other appropriate technologies.
• Develop, validate, and maintain programming solutions for cohort construction, endpoint derivation, analysis dataset creation, and production of tables, listings, and figures.
• Support a broad range of HEOR and real-world evidence studies, including treatment pattern analyses, burden of illness studies, comparative effectiveness and safety research, natural history studies, and external control arm analyses.
• Implement and validate analytical methods specified in study protocols and SAPs, including survival analyses, propensity score approaches, confounding adjustment techniques, and sensitivity analyses.
• Work with complex oncology-focused real-world data assets, including claims, EHRs, genomic testing databases, registries, and linked clinical-genomic datasets, while assessing their quality, completeness, and fitness for purpose.
• Independently perform quality control and validation activities for programming code, analytical datasets, and study outputs, ensuring high standards of accuracy and reproducibility.
• Develop and maintain technical documentation, programming specifications, reusable code, macros, validation tools, and reproducible analytical workflows for assigned studies.
• Collaborate closely with HEOR/RWE scientists, Data Scientists, and Biostatisticians to ensure methodologies are implemented accurately and study objectives are delivered effectively.
• Communicate programming assumptions, implementation decisions, timelines, dependencies, and potential risks clearly to study teams and stakeholders.
• Contribute to real-world programming standards, quality frameworks, and technical best practices while providing guidance and mentorship to junior programmers as appropriate.
• Stay current with evolving industry practices, technologies, and regulatory expectations related to oncology real-world data and evidence generation.

Requirements:

• Hold a BS or MS degree in Statistics, Biostatistics, Computer Science, Data Science, Epidemiology, Mathematics, or another relevant quantitative discipline.
• Bring 8+ years of statistical programming experience in pharmaceutical, biotechnology, CRO, healthcare research, or related environments, with substantial experience operating at a senior level.
• Demonstrate experience independently leading programming activities for observational research, HEOR, epidemiology, or real-world evidence studies from initiation through final deliverables.
• Have strong SAS or R programming expertise, including experience developing analytical datasets and study deliverables from complex healthcare data sources, together with required SQL proficiency.
• Demonstrate working knowledge of R or another programming language for data manipulation, analytics support, and quality control activities where applicable.
• Bring experience developing analysis datasets, tables, listings, and figures from large and complex healthcare or real-world data sources.
• Have experience working with healthcare databases such as claims, EHR, genomic, registry, or linked clinical-genomic datasets, with oncology data experience strongly preferred.
• Possess a strong understanding of observational research workflows and the ability to accurately translate protocols, SAPs, and analytical specifications into programming solutions.
• Demonstrate strong analytical, problem-solving, organizational, and project management skills, with exceptional attention to detail and the ability to manage multiple studies and competing priorities.
• Have excellent written and verbal communication skills and the ability to explain technical decisions, assumptions, risks, and timelines to cross-functional stakeholders.
• Be comfortable working collaboratively in a fast-paced environment while maintaining high standards for technical execution, quality, reproducibility, and continuous improvement.
• Experience with oncology drug development or oncology real-world evidence programs is preferred, as is familiarity with major healthcare data assets such as Flatiron Health, ConcertAI, COTA, Tempus, Guardant, Merative MarketScan, Komodo, Optum, or TriNetX.
• Experience supporting HTA, market access, indirect treatment comparisons, external control arms, or regulatory-grade real-world evidence studies is advantageous.
• Experience developing reusable programming frameworks, standardized macros, validation tools, Git-based version control, and reproducible analytics workflows is also preferred.

Benefits:

• Base salary range of $177,000-$221,000 USD, with individual compensation determined by factors such as skills, experience, education, training, market dynamics, role level, and location.
• Competitive cash compensation as part of a broader total rewards program.
• Eligibility for robust equity awards.
• Comprehensive benefits designed to support employees and their well-being.
• Opportunities for significant learning, professional development, and career growth.
• Remote work opportunity within the United States.
• Opportunity to contribute to advanced real-world evidence programs and collaborate with multidisciplinary experts across analytics, biostatistics, data science, and healthcare research.