Data Scientist

Central Health•Austin, TX

About The Position

The Data Scientist supports Central Health’s mission to improve access to quality care for Travis County residents living at or below 200% of the Federal Poverty Income Level. Working under the guidance of the Principal Data Scientist, this position will help shape and advance the organization’s data science and AI ecosystem, building scalable, ethical, and high-performing models on Central Health’s modern Azure–Snowflake data platform. The Data Scientist will collaborate closely with the Principal Data Scientist, Snowflake Engineer, Snowflake Architect, clinicians, operators and business teams to design, develop, and optimize a data platform that enables advanced analytics, predictive modeling, and AI applications across the enterprise.

Requirements

Doctoral or professional degree in Data Science, Statistics,Computer Science, Mathematics, Engineering, or a related quantitative field
3 years Applied experience in data science, statistical modeling, or machine learning (may include doctoral research). RequiredAnd
1 year Experience working with large, complex healthcare datasets (EHR, claims, population health, or social determinants of health data). RequiredAnd
2 years Demonstrated experience developing and deploying models in a cloud-based environment (Azure, Snowflake preferred). RequiredAnd
3 years Strong proficiency in Python, SQL, and common ML libraries (scikit-learn, TensorFlow, PyTorch, etc.). Required And
3 years Experience with Snowflake, Azure Machine Learning, Databricks, or similar modern data platforms. Required And

Nice To Haves

Experience with Office 365 Suite - Outlook, Excel,Word Preferred

Responsibilities

Partner with the Principal Data Scientist to develop and implement data science and AI models that address clinical, operational, and population health challenges.
Collaborate with the Snowflake Engineer and Architect to ensure that the data environment is optimized for analytics, machine learning, and model deployment.
Design and execute experiments, model training, and validation pipelines using large-scale healthcare data from Epic (Clarity/Caboodle), public health datasets, and other internal/external sources.
Apply advanced statistical and machine learning techniques to identify patterns, forecast trends, and provide actionable insights that improve care delivery and health equity.
Collaborate with analytics, data engineering, and IT teams to ensure reproducibility, scalability, and compliance with data governance, security, and privacy standards (HIPAA, 42 CFR Part 2, etc.).
Contribute to the development of MLOps and AI governance practices to ensure responsible and transparent model lifecycle management.
Communicate analytical findings to technical and non-technical stakeholders through data storytelling, dashboards, and reports.
Mentor analysts and assist with data science literacy efforts across the organization.
Become a data subject matter expert (SME) and understand various sources and applications of Central Health data.
Performs other duties as assigned.