Senior Real-World Data Scientist & Programmer

Syneos Health/ inVentiv Health Commercial LLC; California (MO); On-site; USD 80,600 - 145,000; Full time

Benefits offered by this job

Health benefits

401k matching

Stock purchase plan

Paid time off

Job summary

Syneos Health is seeking a Sr RW Programmer/Sr Data Scientist/Analyst to work on Real World Data in US and UK markets. The role focuses on heavy programming, data review and development of analysis datasets for pharmacoe epidemiology projects.

Experience with Optum, HealthVerity or PharmMetrics is important; SQL, SAS and R are required, with Python optional. Collaboration across epidemiologists and programmers is essential.

Qualifications

• Undergraduate or master's degree in a scientific or statistical discipline.
• Excellent written and verbal communication in English.
• Ability to read, write, speak and understand English.

Responsibilities

• Heavy programming and data review for real-world data analyses using databases like Optum, HealthVerity or PharmMetrics.
• Develop programs and provide statistical programming support for epidemiologists and client needs.
• Ensure outputs meet protocol requirements and quality standards; escalate issues when needed.
• Create analysis datasets, tables, listings and graphs from complex data using SAS, R or SQL.
• Transform healthcare data to a common format using OMOP CDM and document processes thoroughly.
• Collaborate with programmers, biostatisticians and epidemiologists; participate in sponsor meetings as required.

Skills

Analytical thinking

Attention to detail

Education

Bachelor's or Master's in a scientific/statistical discipline

Tools

SAS

R

SQL

Python

OMOP CDM

Job description

Syneos Health is seeking a Sr RW Programmer/Sr Data Scientist/Analyst to work on Real World Data in US and UK markets. The role focuses on heavy programming, data review and development of analysis datasets for pharmacoe epidemiology projects.

Experience with Optum, HealthVerity or PharmMetrics is important; SQL, SAS and R are required, with Python optional. Collaboration across epidemiologists and programmers is essential.