Senior RW Programmer: SAS/R, SQL & Health Data Analytics

Syneos Health/ inVentiv Health Commercial LLC; Boston (MA); On-site; USD 81,000 - 145,000; Full time

Job summary

Syneos Health is seeking a skilled Statistical Programmer to support RW data analyses and epidemiology studies. You will develop programs creating analysis datasets, tables, listings, and graphs, while ensuring data quality and protocol adherence.

Responsibilities include collaboration with epidemiologists, review of outputs, and maintaining thorough documentation. Prior experience with ICD terminology and OMOP CDM is valued, along with strong programming and communication skills.

Qualifications

• Undergraduate or master's degree in biostatistics, epidemiology, or a related scientific field.
• Extensive programming experience in SAS and R; Python or other software is a plus.
• Experience with SQL and data transformation in a RW environment.
• Knowledge of ICD terminology, OMOP CDM, and healthcare data standards.
• Strong communication and collaboration across statisticians, epidemiologists and programmers.

Responsibilities

• Develop programs to create analysis datasets, tables, listings, and graphs.
• Review data and outputs for protocol compliance and data quality.
• Collaborate with epidemiologists and clients to translate study protocols into programming specifications.
• Maintain project documentation and ensure compliance with SOPs and regulatory guidelines.
• Mentor junior programmers and contribute to process improvements.

Skills

SAS

R

SQL

Python

ICD terminology

OMOP CDM

Data review

GLM

Cox model

Propensity score

Education

Undergraduate or master's in biostatistics/epidemiology

Tools

SAS

R

Python

SQL

Job description

Syneos Health is seeking a skilled Statistical Programmer to support RW data analyses and epidemiology studies. You will develop programs creating analysis datasets, tables, listings, and graphs, while ensuring data quality and protocol adherence.

Responsibilities include collaboration with epidemiologists, review of outputs, and maintaining thorough documentation. Prior experience with ICD terminology and OMOP CDM is valued, along with strong programming and communication skills.