The Principal statistician, Data Sciences will:
- Execute the strategy of De-identification Analytics
- Lead a team and serve as a technical leader of the project team in the field of Privacy and De-identification Analytics, with specific expertise in the following areas: statistics, de-identification, risk assessment, and the structure and content of clinical data sets.
- Categorize identifiers and quasi-identifiers, as well as develop the methods to accurately assess re-identification risk and alter data elements to reduce that risk.
- Work in collaboration with business team and/or Business Relationship Manager to understand business demands and identify opportunities.
- Lead and participate in development of software tools, applications, and analyses to support need to ensure patient privacy while maintaining utility.
Additional decision making responsibilities:
- Address complex problems with broad implications for research data, balancing the often-competing needs of privacy and utility.
- Ensure solutions are consistent with business objectives or business strategy.
- Make decisions regarding resource alignment/dedication and prioritization (people resources, dollars/funding, project criticality) and communicate rationale back to the business and project management.
- Contribute to the strategic planning process and long-term direction for the Privacy and De-identification team and aligns plans between stakeholders.
- A Bachelor’s degree with a minimum of 7 years of relevant experience OR an advanced degree (Master’s, PhD or MD) in Statistics or related discipline with a minimum of 5 years of relevant experience is required.
- Familiarity with tools and methods to calculate re-identification risk in clinical data is preferred.
- Experience building population statistics to compare to the prevalence of elements in the analysis dataset is preferred.
- Experience working with complex, multidisciplinary teams in a matrix environment is required.
- Strong data modelling and schema design experience and working knowledge of relational database modeling concepts and SQL is required.
- Experience using data profiling / quality tools, experience with ETL activities, knowledge of common data models (e.g. OMOP, i2b2) is preferred.
- Understanding of clinical data model/standards/vocabularies such as MEDRA, SNOMED, CDISC, CDM and RxNORM is preferred.
- Experience working in a data warehouse environment with exposure to INFORMATICA, Redshift and Teradata. Knowledge of health outcomes databases (claim, EMR/EHR, survey, observation studies) is preferred.
- Strong expertise in health informatics, including familiarity with health outcomes databases, clinical trial registries Understanding of IT resource and cost drivers for a franchise or business unit is required.
- Excellent interpersonal skills and able to drive tasks in a diverse team is required.
Requisition ID: 4089171105