Associate Data Scientist
VNS Health
- USA
- $85,000-106,300 per year
- Permanent
- Full-time
- Referral bonus opportunities
- Generous paid time off (PTO), starting at 30 days of paid time off and 9 company holidays
- Health insurance plan for you and your loved ones, Medical, Dental, Vision, Life and Disability
- Employer-matched retirement saving funds
- Personal and financial wellness programs
- Pre-tax flexible spending accounts (FSAs) for healthcare and dependent care
- Generous tuition reimbursement for qualifying degrees
- Opportunities for professional growth and career advancement
- Internal mobility, generous tuition reimbursement, CEU credits, and advancement opportunities
- Participates in end-to-end analysis that includes data gathering from internal and external sources, specifying requirements, processing, compiling, validating, modelling and presenting data.
- Inspects data quality throughout all stages of acquisition and processing, including data sourcing/collection, ground truth generation, normalization, and transformation; alerts Data Science management as issues arise.
- Solves routine, inter-disciplinary analysis problems by applying analytical methods as needed.
- Presents data and results with meaningful visualizations and tables to the Data Science Team.
- Meets with clinical operations, business owners, and/or IT to understand how VNS Health applications enter and commit data records into database systems.
- Responds to business requests with descriptive reports in a timely manner. Uses ad-hoc requests to gain knowledge of business and data systems.
- Ensures the accuracy of work and the meaningful interpretation of the statistical inference.
- Participates in developing analytic plans, including statistical design and methodology; executes analysis as specified, creates final reports, and presents findings to business management.
- Participates in special projects and performs other duties as assigned.
- Master's Degree in Statistics, Biostatistics, Mathematics, Data Science, Econometrics, Epidemiology or other statistics related degree required
- Experience with using statistical software (e.g. R, Python, Julia, MATLAB, SAS, or STATA) required
- Effective oral, written and interpersonal communication skills required
- Knowledge of relational databases and programming experience in SQL preferred
- Experience with R-Shiny and business intelligence applications preferred
- Experience with medical claims and health assessment data (e.g. OASIS, UAS-NY) preferred
- Knowledge of Medicare and Medicaid payment policy and alternative payment models (e.g. BPCI, PDGM Value Based Payments, dual-risk models, Hospice Final Rule) preferred
- Hands on experience building and deploying predictive models (API, database ETL, R/Python application integration to BI or ETL tools), specifically in a health care setting preferred
- Application of quasi-experimental methods to health care data preferred