Senior RWD (Real World Data) Data Scientist-remote

Are you interested in working directly for a single sponsor while having the security and additional career opportunities that working for a global CRO can bring? Our team says it’s the best of both worlds...

ClinChoice is searching for aSenior RWD Data Scientist  to join one of our clients. 

ClinChoice is a global full-service CRO with a strong focus on quality, professional development, and supportive culture. As a client-facing role, we are looking for confident candidates with the ability to work independently whilst establishing a high-trust environment with the client’s counterparts.  

Primary Duties

Lead development of analysis specifications, develop programs, and conduct analyses while providing technical guidance for Real World Data (RWD) research. Ensure quality standards and methodological rigor across projects through development of patient cohorts and validation of key variables.

Required Experience: 
• Leadership of RWD analysis strategy and execution
• Lead development of technical specifications and study methodology
• Statistical programing proficiency (R, SAS, SQL., Python)
• Oversight of quality control processes
• Cross-functional team collaboration
• Management of project timelines and deliverables
• Development of best practices and standards
• Demonstrated ability to communicate complex analyses to non-technical stakeholders
• Technical Expertise o Proficiency in SAS or R & SQL is a must, expectation to be programming independently, creating packages, taking requirements, writing specifications, work with complex data structures and study design. o Experience in more complex programming, such as propensity score analysis, lines of therapy, Sankey diagram, machine learning o Experience with complex statistical programing, such as propensity score matching o Experience applying machine learning methods (such as LASSO, DT, RF, and XGBoost) with RWD
• Experience with OHDSI or DARWIN tool sets in RSubject Matter Expertise o Understanding of epidemiology / outcomes research, experience with study design and execution, Biomarker/genomic data sources.

Experience with healthcare databases:
Claims (examples include Optum, MarketScan, Pharmetrics+, HealthVerity, CPRD)
Electronic Health Records (examples include IQVIA, Flatiron, Concert AI, TriNetX)
Experience with OMOP CDM or similar common data model framework o Knowledge of US/international data sources 
For clinical trial analysis specifically, experience with psychometric validation Project Implementation capability (reviewing, contributing to technical review and suggesting edits, executing) in the following are expected o Statistical analysis plan development 
Protocol / manuscript development o Study design and execution
Being able to track and update work in a software (Jira or ADO) 

Minimum Qualifications

• Master’s degree is Biostatistics, Epidemiology, Data Science, Bioinformatics, or related field with 5-8 years of relevant post-graduation experience or PhD with 3+ years post-graduation experience
• Advanced expertise in statistical programming and observational research methods
• Comprehensive experience with healthcare data sources and analysis
• Proven ability to lead projects autonomously in a matrix environment
• Track record of managing priorities and performance targets 
  
  Additional requirements may include:
  
  Oncology Specific: Experience in oncology observational studies, experience in Flatiron and ConcertAI, understanding of programming logic in lines of therapy
  
  Molecular Epi Specific:
  CCloud-based SQL is desirable
  Experience with Clinico-genomic multi-modal data (e.g. Tempus AI) or population biobank data (UK biobank)
  Experience and comfort to multitasking and working in a matrix environment
  Tableau or Power BI or other graphics tool is a plus
  
  HEOR Specific:
  SAS/SQL required, additional experience with R beneficial
  Experience with health economics and outcomes research (HEOR) methodologies, including cost analysis, burden of illness studies, and comparative effectiveness research.

 

The Applicati