Associate Director, Real-World Analytics Programing

revolutionmedicines; United States; Remote; USD 177,000 - 221,000; Full time

Benefits offered by this job

Remote-eligible position

Equity awards

Benefits

Job summary

revolutionmedicines is seeking a Lead Statistical Programmer for real-world evidence and health economics studies in oncology. You will independently manage programming from kickoff to final deliverables, translating study designs into reproducible analytic solutions across claims, EHR, and genomic datasets.

You will lead programming deliverables, review SAPs and protocols, and develop robust analytics using SAS, SQL, R, and Python while mentoring junior programmers.

Qualifications

• Bachelor's or advanced degree in statistics, biostatistics, computer science, or related field; master's preferred.
• Significant experience as a lead statistical programmer for real-world evidence, health economics, or observational studies.
• Strong proficiency in SAS, SQL, R, and Python for reproducible analytics.

Responsibilities

• Serve as the lead statistical programmer for assigned real-world studies from initiation to final delivery.
• Lead programming deliverables: analysis datasets, table/listing/figure shells, validation plans, documentation, and final outputs.
• Review SAPs, SAPs, and analysis specifications to ensure accurate implementation of requirements.
• Develop, validate, and maintain SAS, SQL, R, Python solutions for cohort construction, endpoint derivation, and study outputs.
• Generate and QC analysis datasets, tables, listings, and figures per protocols and standards.
• Implement analytic methods per protocols and SAPs, including survival analyses and propensity score approaches.
• Work with claims, EHR, and genomic datasets; assess data quality and fitness-for-purpose.

Skills

Statistical programming

Leadership

SAS

SQL

R

Python

Reproducible analytics

Study documentation

Version control

Education

Bachelor's or master's in statistics/biostatistics/computer science

Tools

SAS

SQL

R

Python

Git

Job description

Role overview

A lead statistical programming role within a real-world evidence and health economics function supporting oncology research. The position independently manages programming activities for observational studies from kickoff through final deliverables, translating study designs into reproducible analytic solutions. The work spans a broad portfolio including treatment pattern analyses, burden of illness studies, comparative effectiveness and safety research, natural history studies, and external control arm analyses.

Responsibilities

• Serve as the lead statistical programmer for assigned real-world studies, managing activities from initiation through final delivery.
• Lead programming deliverables including analysis dataset specifications, table, listing, and figure shells, validation plans, programming documentation, and final study outputs.
• Review study protocols, statistical analysis plans, and analysis specifications to ensure accurate implementation of requirements.
• Develop, validate, and maintain SAS, SQL, R, Python, and other programming solutions for cohort construction, endpoint derivation, analysis dataset creation, and study deliverables.
• Generate and quality-control analysis datasets, tables, listings, and figures in accordance with protocols, SAPs, and internal standards.
• Implement analytic methods specified in protocols and SAPs, including survival analyses, propensity score approaches, confounding adjustment methods, and sensitivity analyses.
• Work with oncology-focused real-world data assets such as claims, electronic health records, genomic testing databases, and linked clinical-genomic datasets.
• Assess data quality, completeness, and fitness-for-purpose and communicate recommendations, assumptions, timelines, and risks to study teams.
• Contribute to real-world programming standards, quality frameworks, and reusable code, providing technical guidance to junior programmers as needed.

Requirements

• Bachelor's or advanced degree in statistics, biostatistics, computer science, or a related quantitative field; master's preferred.
• Significant experience as a lead statistical programmer supporting real-world evidence, health economics and outcomes research, or observational studies.
• Strong proficiency in SAS, SQL, R, and Python for reproducible analytics.
• Demonstrated experience with study documentation including protocols, SAPs, and analysis specifications.
• Experience working with claims, electronic health record, or genomic datasets.
• Familiarity with Git or other version control systems and reproducible analytics workflows.

Nice to have

• Experience developing reusable programming frameworks, standardized macros, and validation tools.
• Experience working in a fast-paced and growing biotechnology organization.

Benefits and work setup

• Remote-eligible position with a published base pay range of $177,000 to $221,000 USD, plus competitive equity awards and benefits.
• Opportunities for learning and development as part of a broader total rewards program.