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About the Role

Join a team dedicated to advancing prevention on a global scale through next-gen science, mRNA innovation, and AI-driven breakthroughs in Vaccines. The Data Assessment Center of Excellence (CoE) ensures Sanofians use the right data, the right way, for real patient impact by establishing enterprise-wide standards for RWD assessment and supporting cross-functional teams with expert guidance on data source selection and usage.

Responsibilities

Design and execute rigorous data assessment frameworks to evaluate the fitness-for-purpose of real-world data (RWD) sources.
Support the development of reliable RWD Foundation and Products.
Serve as a methodological authority and RWD data domain expert.
Ensure best-in-class data selection and optimal data usage for reliable insights or evidence generation.
Lead and execute feasibility assessments for RWD sources (EHR, claims, registries, wearable/digital health data).
Develop and apply structured data assessment frameworks to evaluate data quality dimensions.
Assess the availability and representativeness of patient populations within RWD sources.
Evaluate the feasibility of extracting structured and unstructured data elements from EHR systems.
Document assessment outcomes in standardized feasibility reports and communicate findings to stakeholders.
Identify and articulate limitations of RWD sources.
Design methodologically sound recommendations to minimize misuse of RWD.
Ensure appropriate use of medical coding standards for patient identification and phenotyping.
Apply advanced epidemiological and biostatistical methods.
Provide methodological input on the use of clinical score proxies and surrogate endpoints.
Provide methodology advises ensuring deliverables from RWD Foundation, RWD Science, and RWD Products are based on medical evidence/guidelines.
Work closely with analysts & data scientists to ensure methodological recommendations are realistic and implementable.
Partner with R&D, Business units, and Digital teams on data identification and appropriate usage of RWD.
Serve as the methodological point of contact for fit-for-purpose data assessment inquiries.
Collaborate with RWD Foundation, RWD Product Owners, and RWD Data Sciences.
Manage external data vendors and technology partners.

Requirements

Advanced degree (Master's or PhD) in Epidemiology, Biostatistics, Health Informatics, Health Economics, Pharmacoepidemiology, or a closely related quantitative discipline.
Minimum 4-5 years (Master's) or 2-4 years (Doctoral) of relevant experience in real-world data, commercial analytics, real-world evidence, health outcomes research, fit-for-purpose feasibility assessment, data quality assessment, or a related field within the pharmaceutical, biotech, or health technology industry.
Experience in predictive modeling using RWD to identify at-risk patient populations with a publication record in peer-review journals.
Experience in patient & healthcare provider segmentation to inform Medical and Commercial strategy.
Demonstrated expertise in epidemiological study design and statistical methods.
Strong proficiency in statistical programming languages: SQL, Python, R, and/or SAS.
Solid working knowledge of Snowflake for database querying and data extraction.
Familiarity with medical coding systems: ICD-10, CPT, SNOMED CT, LOINC, RxNorm.
Experience/knowledge on OHDSI OMOP CDM standardized data model for healthcare data.
Understanding of US EHR, claims, disease registry data, public health surveillance data as well as US healthcare billing system.
Experience with AI coding tools such as Cursor, GitHub Copilot, Claude, LLM.
Knowledge of automation tools such as Power Automate, Power App (an asset not required).
Requires a high level of interactive communication with diverse stakeholders.
Can work with assumptions & in a fast-paced environment.
Proven teamwork and collaboration skills.

Skills

Real-world data assessment
Fitness-for-purpose data evaluation
Data quality assessment
Epidemiology
Biostatistics
Health Informatics
Health Economics
Pharmacoepidemiology
Predictive modeling
Statistical methods (propensity score matching, regression analysis, etc.)
SQL
Python
R
SAS
Snowflake
Medical coding systems (ICD-10, CPT, SNOMED CT, LOINC, RxNorm)
OHDSI OMOP CDM
US EHR data
US claims data
US disease registry data
US public health surveillance data
US healthcare billing system
AI coding tools (Cursor, GitHub Copilot, Claude, LLM)
Automation tools (Power Automate, Power App)

Location

Toronto, ON

Work Type

Onsite

Experience Level

Minimum 4-5 years for Master's degree holder or 2-4 years for Doctoral degree holder of relevant experience

Education Level

Advanced degree (Master's or PhD) in Epidemiology, Biostatistics, Health Informatics, Health Economics, Pharmacoepidemiology, or a closely related quantitative discipline

Salary/Compensations

127,000.00 - 177,000.00 (Includes target bonus)

Benefits

High-quality healthcare
Prevention and wellness programs
At least 14 weeks’ gender-neutral parental leave

About the Company

Sanofi is an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth.
Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world.
Together, we chase the miracles of science to improve people’s lives.

Equal Opportunity

Sanofi is an equal opportunity employer committed to diversity and inclusion.
Our goal is to attract, develop and retain highly talented employees from diverse backgrounds, allowing us to benefit from a wide variety of experiences and perspectives.
We welcome and encourage applications from all qualified applicants.
Accommodations for persons with disabilities required during the recruitment process are available upon request.
At Sanofi, we provide equal opportunities to all regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, ability or gender identity.