Data Scientist, Public Health Data Linkage (DSIS 3) DOH8949

State of Washington•Multiple Locations Statewide, WA

3d•Remote

About The Position

This recruitment is open to Washington residents and those residing on the ID/WA and OR/WA borders. The Opportunity As a Data Scientist you will work within the Linkage and Integrated Data Analysis (LIDA) Unit within the Center for Health Statistics (CHS). The LIDA Unit develops advanced data linkage methods that improve the quality, accuracy, and usability of public health data used to support research, surveillance, and decision making across Washington State. In this role, you will lead complex data science projects that combine machine learning, statistical modeling, data engineering, and informatics to connect and analyze large, complex datasets. You will develop and evaluate data linkage models, build automated analytical pipelines, improve data quality, and explore innovative approaches that strengthen the Center's data modernization efforts. You'll also serve as a technical expert, collaborating with epidemiologists, informaticists, data scientists, and public health partners on complex analytical initiatives. Your work will strengthen the systems used to connect vital records and other health data, providing reliable information that helps identify health trends, improve data quality, and support evidence based public health decisions that protect and improve the health of people across Washington.

Requirements

Seven (7) years of experience developing, analyzing, or implementing advanced data science, machine learning, statistical modeling, or data engineering solutions using large and complex datasets.
A bachelor's degree in data science, computer science, statistics, biostatistics, mathematics, informatics, public health informatics, epidemiology, engineering, or another closely related quantitative field; AND Five (5) years of experience developing, analyzing, or implementing advanced data science, machine learning, statistical modeling, or data engineering solutions using large and complex datasets.
Experience using Python to develop or evaluate machine learning models, automate data processing, or analyze large and complex datasets.
Experience using SQL to extract, transform, integrate, and analyze large datasets.
Experience developing, implementing, or evaluating machine learning or data linkage models.
Experience developing or maintaining automated data processing or analytical pipelines.
Experience evaluating data quality, validating analytical outputs, and performing quality assurance.
Experience in applying statistical analysis or modeling techniques to large, complex datasets.
Experience leading complex data science or analytics projects or serving as a technical subject matter expert.
Experience communicating technical findings and recommendations to technical and nontechnical audiences.

Nice To Haves

Master’s degree or higher in informatics, data science, mathematics, computer science, statistics, biostatistics, epidemiology, social science, or related technical or quantitative field
Experience building machine learning models using tools such as R, Python, Julia, Rust, Databricks, or similar technologies.
Experience working with large SQL-based databases.
Experience developing binary classification machine learning models, including feature engineering using raw or unstructured data.
Experience building, maintaining, or evaluating machine learning data linkage or entity resolution projects.

Responsibilities

Lead complex analyses of linked public health data using advanced statistical methods, machine learning, and data science techniques to answer challenging analytical questions.
Design, evaluate, and improve machine learning and AI driven data linkage models, ensuring high quality, accurate, and equitable results.
Develop and maintain automated data engineering and analytical pipelines using programming languages such as Python and SQL to support large scale data integration and analysis.
Acquire, process, and standardize structured and unstructured data from administrative and open source data sources to strengthen data linkage performance and quality assurance.
Research, test, and implement emerging data science methods that improve interoperability, entity resolution, and public health data modernization.
Serve as the technical expert for data linkage and machine learning by providing consultation, mentoring colleagues, and collaborating with internal and external partners on complex projects.
Communicate analytical findings and technical recommendations to a variety of audiences to support data informed public health decisions.
Contribute technical expertise during public health emergency response activities and support critical analytical needs when required.