Senior RWE Statistical Programmer

Cytel; Hartford (CT); On-site; USD 130,000 - 170,000; Full time

Job summary

Cytel Inc. in the United States is seeking a senior epidemiology data scientist to contribute to RWE analytics for pharma, CRO, or academic partners. You will prepare Real World data, guide analytic strategies, and support stakeholders across projects.

The role involves programming statistical analyses, data linkage, and generating tables/figures for study reports, presentations, and regulatory documents. Strong SQL, SAS or R, and experience with large observational datasets are essential.

Qualifications

• Master’s degree or PhD in epidemiology, biostatistics, statistics, bioinformatics, economics with 5+ years in RWE analytics.
• Proficiency in SQL; SAS or R proficiency required.
• Experience analyzing RWE sources such as Optum Datamart, Truveta, and UK Biobank is preferred.

Responsibilities

• Provide support to the Epidemiology team by preparing Real World data and advising on analytic strategies.
• Program and conduct statistical analyses under supervision using statistical packages.
• Support data standardization, visualization, and reporting of observational data.
• Partner with epidemiologists to manage stakeholder relationships and ensure timely project delivery.
• Develop study protocols and analysis plans leveraging large RWD sources.
• Present results to clients and assist in study reports.

Skills

SQL

SAS/R

RWE analytics

data analysis

project management

communication

Education

Master's or PhD in related field

Tools

SAS

R

Job description

Cytel Inc. in the United States is seeking a senior epidemiology data scientist to contribute to RWE analytics for pharma, CRO, or academic partners. You will prepare Real World data, guide analytic strategies, and support stakeholders across projects.

The role involves programming statistical analyses, data linkage, and generating tables/figures for study reports, presentations, and regulatory documents. Strong SQL, SAS or R, and experience with large observational datasets are essential.