[Hiring] Data Scientist, Public Health Data Linkage @State of Washington

Role Description

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.

Key Responsibilities Include:

• 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.

Qualifications

• You enjoy solving complex problems and are motivated by work that combines advanced analytics with meaningful public service.
• You are comfortable leading technical projects, exploring new approaches, and translating complex analytical concepts into practical solutions.
• You value collaboration, welcome diverse perspectives, and communicate effectively with both technical and nontechnical audiences.
• You are curious, thoughtful, and committed to continuously improving how public health data is collected, connected, and used to support healthier communities 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.

Preferred Qualifications

• 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.

Benefits

• Comprehensive medical, dental, and vision coverage.
• Life and long-term disability insurance.
• Flexible spending and health savings accounts.
• Retirement plans.
• Paid holidays, vacation, and sick leave.
• Dependent care assistance and professional development opportunities.

Working Conditions

• This position's work can be performed fully remotely. No regular in-person attendance is required.
• Exposure to hazards is limited to those commonly found in indoor at home or office environments.
• This position is sedentary, working at a computer for extended periods.
• The position requires repetitive use of a computer, inputting data and navigating a database, creating and modifying electronic documents, and using email and the internet.
• This position has a work schedule of 40 hours per week; however, the position may be expected to work longer hours to complete projects or assignments.
• Travel is not required to perform the duties of this position; however, occasional travel may be expected to attend meetings, trainings, or conferences.

Application Directions

• Only materials submitted through the official application will be considered. Emailed resumes or documents won’t be accepted.
• Click “Apply” to complete your application. Attach your resume, cover letter, and DD-214 (if applicable).
• List at least three professional references, including a supervisor, a peer, and someone you’ve supervised or led (if applicable).
• DO NOT INCLUDE private details like your SSN or birth year, personal photos, transcripts, certifications, diplomas, projects, portfolios, or letters of recommendation.