Having at least 5 – 8 years of experience in industry and solidly collaborative interpersonal, a Senior Data Scientist knows, appropriately selects and deftly uses the tools of the craft—data ingesting, data cleansing, feature engineering, data filtering and aggregating, statistical estimation and hypothesis testing, machine learning and iterative development and continuous production integration and deployment—to support GWT’s Medicaid clients, by wrangling healthcare and other client data assets and then analyzing them iteratively to surface complex, impactfully actionable insights. Prior experience with healthcare is strongly preferred, but can be offset with clear, integrative strength with data; and at all events, learning this content domain starting day one is part and parcel of the on-going task.
Must Have:
- Expert knowledge of SQL queries to process large amounts of data in a set-based fashion
- Thorough understanding of various SQL windowing functions through regular use
- Has worked frequently with datasets at least 10M rows in size, some of them ugly/messy
- Solid python, including having developed object-oriented designs
- Solid knowledge of Statistical Estimation, Machine Learning, Overfit, False Discovery, etc.
- Solid experience with the use of Dev\Sec\Ops procedures tools for iterative development and CI/CD
- Main-stream BI dashboarding tools such as PowerBI, Tableau, SAS, etc.
- Excellent written and verbal communication skills
- Frequently Occurring Plusses This Level:
- Solid understanding of indexing, stored procedures, materialized views, etc.
- Performed Data Science with Healthcare data
- Functional Programming
- Experience doing Data Science leveraging the elasticity in a major Cloud environment
- Has good knowledge of Repeated Measures Statistical methods including forecasting
- Explainable Machine Learning and Artificial Intelligence / Neural Network Experience
- Has worked with datasets 100M – 10B rows in size, some of them ugly/messy
- Performance Optimization for Data Science development and in production
- Knowledge of Semi-Structured and UnStructured data, schema-on-read, parsers, NLP packages
- Comfort-level presenting to business stakeholders and executives
Please Highlight any of these more Advanced Levels of Experience:
- Working knowledge of stacks and CQRS data structures, and state machines that use them
- Use of a Massively Parallel Database Environment
- Understands how to optimize data models for MPP with distribution keys and schemes
- Has used DataBricks for Data Science - knowledge of Scala a plus
- Solid Experience Deriving Insights from Healthcare data
- Experience working toward replicable causal inference in repurposed data
- Medical Training / Experience in Practice