Senior Data Scientist

They will manage and mentor other more junior data scientists and are distinguished from Data Scientists both in years of experience and by providing leadership in introducing new methods and supporting infrastructure.

They may need to work with data engineers, data modelers, business intelligence analysts and IT staff to set up more complex ongoing analyses that feed dashboards or other data products.

Experience
This Classification must have a minimum of five (5) years of relevant experience in mathematical modeling, statistical analysis, machine learning, AB testing, or data science in an applied context using statistical programming languages, SQL, and other scripting and statistical tools as well as proficiency in one or more visualization tools.

And Education

This classification requires the possession of a master''s degree or higher in economics, statistics, math, engineering, science, social science, data science or other quantitative focused field. Additional two (2) years of qualifying experience may be substituted for the required education along with demonstrated completion of training, bootcamps, or supplemental coursework in mathematical modeling, statistical analysis, and machine learning methods.

Entity-relationship modeling

Master data management concepts.

SQL or PySpark

 Star Schema modeling

 Databricks 

Technical Skills

MUST HAVE: Strong SQL expertise, including writing complex queries

MUST HAVE: Experience with Databricks and lakehouse / medallion architecture

MUST HAVE: Dashboard development using Tableau or Power BI

MUST HAVE: Experience with data pipelines, ingestion, and performance monitoring

MUST HAVE: Familiarity with cloud-based data environments (AWS)

Experience with RDS or similar relational database systems

MUST HAVE: Data validation and reconciliation at scale

MUST HAVE: Data analytics and ability to work with large, complex datasets

Understanding of machine learning concepts (hands-on experience preferred but not required)

Experience with or exposure to A/B testing

DevOps exposure (preferred)

MUST HAVE: Ability to decode technical data structures and explain them clearly

Experience working with patient data or healthcare datasets (preferred)

 Non-Technical / Functional Skills

Ability to interpret program data, walk through datasets, and make sense of ambiguous information

Solid understanding of data governance principles and participation in governance processes

Ability to connect technical systems → program → clinical operations

Comfort supporting multiple divisions and cross-functional teams

Experience identifying solutions and making recommendations

Ability to understand where data originates and how it flows through the organization

Skilled in developing clear, actionable dashboards for business users

Able to work independently to troubleshoot and validate data issues

Soft Skills

Strong communicator with excellent presentation skills, including presenting to executive-level stakeholders

Collaborative—works well across teams and functions

Personable and able to work with diverse personalities

Independent and self-sufficient; doesn’t require heavy oversight

Solution-oriented mindset with strong analytical thinking

Comfortable with large teams, diverse working styles, and fast-moving environments

Ability to stay calm and effective when dealing with complexity or ambiguity