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.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
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