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Sr Programmer Sr Data Scientist​/Analyst OMOP; NA & UK

Job in Toronto, Ontario, C6A, Canada
Listing for: United States Digital Space LLC
Full Time position
Listed on 2026-06-15
Job specializations:
  • IT/Tech
    Data Scientist, AI Engineer (Applied/Software)
Job Description & How to Apply Below
Position: Sr Programmer Sr Data Scientist/Analyst OMOP (NA & UK Only)

Updated: Yesterday

Location: Toronto, ON, Canada

Job : -OTHLOC-1510-2DR

Job Responsibilities
  • Must be located in the United States, Canada or UK with no sponsorship needs to be considered for this position.
Key Responsibilities OHDSI / DARWIN Analytics & Implementation
  • Collaborate with researchers to understand project requirements and translate them into OHDSI/DARWIN-compatible solutions.
  • Build, validate, and execute OMOP CDM cohorts and analyses using ATLAS (cohort definition, characterization, exploration), ATHENA (vocabulary browsing, concept sets), ACHILLES (data characterization and quality insights), and R packages in the OHDSI/DARWIN ecosystem (for cohort execution, characterization, estimation, and related workflows).
  • Perform analyses using ATLAS and/or Prometheus or via programmatic workflows in R (and Python where appropriate), depending on study needs and platform patterns.
  • Customize and extend OHDSI tools and applications as needed to support project- or portfolio-specific requirements.
  • Incorporate AI-assisted workflows to improve efficiency in: code generation/refactoring, validation and QA checks, documentation and study write-ups, exploratory analysis and summary generation while ensuring results remain transparent, traceable, and scientifically defensible.
Observational Study Design, Statistics, and AI/ML Awareness
  • Apply and document observational study designs and epidemiologic concepts for RWE (e.g., descriptive epidemiology, cohort designs, self-controlled designs, comparative approaches as applicable).
  • Implement and interpret appropriate statistical methods, including confounding control strategies, time-to-event approaches, sensitivity analyses, and fit-for-purpose evaluations.
  • Maintain familiarity with machine learning and statistical concepts to support exploratory modeling, feature engineering, prediction workflows (when relevant), and method selection.
Reproducible, AI-Enabled, Production-Grade Analytics
  • Develop reusable and maintainable analytic code, prioritizing reproducibility and auditability (clear methods, parameterization, and structured outputs).
  • Incorporate AI-assisted workflows to improve efficiency in: code generation/refactoring, validation and QA checks, documentation and study write-ups, exploratory analysis and summary generation while ensuring results remain transparent, traceable, and scientifically defensible.
Git Hub-Centric Collaboration
  • Use Git Hub extensively (branching, pull requests, code reviews, issue tracking) to deliver collaborative, production-grade analytics.
Required Qualifications
  • Masters degree in Statistics or related field.
  • Demonstrated experience with OMOP CDM and OHDSI tooling, including ATLAS (or Prometheus), ATHENA, and ACHILLES.
  • Proficiency in common OHDSI community languages: SQL and R. Python is good too but most open-source tooling is in R.
  • Strong understanding of observational study design and epidemiologic concepts, with emphasis on RWE.
  • Experience working with healthcare data such as EHR and insurance claims, including healthcare data standards and fit-for-purpose evaluation.
  • Solid understanding of clinical terminologies such as SNOMED, ICD-9/10, CPT, HCPCS, READ and related standard vocabularies used in OMOP.
  • Experience with data quality assessment and data validation techniques.
  • Proven ability to work in a fast-paced environment, delivering high-quality outputs with strong documentation and collaboration.
  • Strong problem-solving ability and comfort working in cross-functional teams.
  • Excellent communication skills, with the ability to convey technical concepts to technical and non-technical stakeholders.
  • Strong experience developing and maintaining documentation for RWE studies and insight generation.
  • Demonstrated willingness and ability to incorporate AI tools into workflows for efficiency and quality.
  • Experience supporting federated/network study execution patterns (where applicable).
Benefits
  • Company car or car allowance.
  • Health benefits to include Medical, Dental and Vision.
  • Company match 401k.
  • Eligibility to participate in Employee Stock Purchase Plan.
  • Eligibility to earn commissions/bonus based on company and individual performance.
  • Flexible paid time off (PTO) and sick time (eligibility may vary depending on location).
  • Compliance with all applicable federal, state, and municipal paid sick time requirements.
Salary Range

The base salary range represents the anticipated low and high of the Syneos Health range for this position. Actual salary will vary based on various factors such as the candidate’s qualifications, skills, competencies, and proficiency for the role.

Additional Information

Tasks, duties, and responsibilities as listed in this job description are not exhaustive. The Company, at its sole discretion and with no prior notice, may assign other tasks, duties, and job responsibilities. Equivalent experience, skills, and/or education will also be considered so qualifications of incumbents may differ from those listed in the Job Description. The Company, at its…

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