Sr RW Programmer / Sr Data Scientist / Analyst – Real World Data
Company: Syneos Health
Location: USA (NY – Remote) / UK Only
Job ID: 25108521
Work Authorization: US/UK only (No sponsorship)
Updated: Yesterday
1. Role Overview
This role focuses on real-world data (RWD) programming and advanced analytics supporting epidemiology and real-world evidence (RWE) studies.
The position is highly programming-intensive, involving healthcare claims and EHR data, statistical modeling, and protocol-driven analysis.
2. Core Responsibilities
A. Programming & Data Development
Develop analytical programs using:
SAS
R
Python
SQL (mandatory)
Create:
Analysis datasets
Summary tables
Listings and graphs
Support real-world data transformations and study deliverables
B. Real-World Data Work
Work with large healthcare datasets:
Optum
HealthVerity
IQVIA Pharmetrics
Nice-to-have:
MarketScan
Medicaid / Medicare
VA data
Handle:
EHR data
Claims data
Strong knowledge of:
ICD coding systems
Clinical terminology
C. Study Design & Protocol Support
Interpret and support:
Study protocols
Statistical Analysis Plans (SAPs)
Define and implement:
Cohort derivation logic
Index date definitions
Follow-up periods
Review programming outputs against protocol requirements
Identify and escalate discrepancies
D. Statistical & Advanced Modeling
Apply statistical methods including:
GLM (Generalized Linear Models)
Logistic regression
Cox proportional hazards models
Propensity score matching
Incidence rate calculations
Address complex and messy real-world datasets
E. Data Standards & Transformation
Work with:
OMOP Common Data Model (CDM)
Transform raw healthcare data into standardized analytical formats
Ensure consistent dataset structure for analysis and reporting
F. Quality, Compliance & Validation
Ensure compliance with:
SOPs
ICH guidelines
Perform validation programming
Maintain inspection-ready documentation
Resolve discrepancies with:
Epidemiologists
Biostatisticians
Programming teams
G. Collaboration & Communication
Participate in:
Sponsor meetings
Kickoff meetings
Communicate:
Progress updates
Issues and risks
Contribute to:
Study planning discussions
Programming strategy
Support mentoring and knowledge sharing
3. Required Qualifications
Education
Bachelor’s or Master’s degree in:
Biostatistics
Epidemiology
Mathematics
Other related scientific/statistical field
Technical Skills
Strong experience in:
SAS OR R
Python (preferred)
SQL (required)
Experience in real-world data environments
Domain Expertise
Claims + EHR data experience
ICD coding knowledge
Cohort building experience
Understanding of study timelines and follow-up design
Ability to work with messy healthcare data
4. Preferred Skills (Nice-to-Have)
AI/ML experience (workflow automation, LLMs)
GitHub / version control experience
Advanced machine learning modeling
Multi-database healthcare exposure
OMOP CDM expertise
5. Work Expectations
Manage multiple projects simultaneously
Strong time management under deadlines
Ability to adapt to shifting priorities
Independent problem-solving mindset
Strong documentation discipline
6. Key Soft Skills
Strong communication skills
Attention to detail
Cross-functional collaboration
Ability to explain technical findings clearly
Proactive issue identification and escalation
7. Role Impact
Supports real-world evidence generation (RWE) for healthcare decision-making
Enables epidemiology and clinical research teams with high-quality data insights
Contributes to regulatory and sponsor-level analytics
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