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

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

Salary

$105,612.00 - $142,020.00 Annually

Location

Multiple Locations Statewide, WA

Job Type

Full Time - Permanent

Remote Employment

Remote Only

Job Number

DOH8949

Department

Dept. of Health

Division

Disease Control and Health Statistics (DCHS)

Opening Date

08/03/2026

Closing Date

8/9/2026 11:59 PM Pacific

Salary Information

The high end of the salary range, Step M is typically a longevity step

• Description
• Benefits
• Questions

Description

Data Scientist, Public Health Data Linkage (DSIS 3)

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 Centers data modernization efforts. Youll 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.

Why You'll Love This Role:

• Work with cutting edge data science, machine learning, and data engineering technologies to solve complex public health challenges.
• Lead innovative projects that shape how public health data is integrated, analyzed, and modernized across Washington State.
• Improve the quality, accuracy, and accessibility of health data that supports research, surveillance, and evidence-based decision making.
• Collaborate with experts across epidemiology, informatics, and public health to build data solutions that strengthen programs serving communities throughout Washington.

What You Bring:

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.

Minimum Qualifications

There are multiple pathways to qualify for this position. You must meet one of the options provided and any additional criteria listed. Experience may have been gained through paid or unpaid activities. Please ensure any relevant experience defined below is outlined in your cover letter, resume, and/or applicant profile.

Option 1: 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.

Option 2: A bachelors 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.

Additional Required Knowledge, Skills, Abilities, and Experience

• 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.

PreferredQualifications

While these aren't required, having them can help you stand out as a candidate.

• 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.

Employee Benefits

We offer a solid benefits package that supports you and your family's health, financial security, and work-life balance. You'll have access to comprehensive medical, dental, and vision coverage, life and long-term disability insurance, flexible spending and health savings accounts, and retirement plans that help you plan for tomorrow while you're living today. Paid holidays, vacation and sick leave help you recharge, and additional programs like dependent care assistance and professional development opportunities add value beyond basic coverage. Join us and enjoy benefits designed to care for you as much as you care about public health. Learn more about DOH benefits and see how we support your life at work and beyond by visiting Work@Health.

About the Center for Health Statistics

The Center for Health Statistics (CHS), within the Division of Disease Control and Health Statistics, collects, manages, and analyzes Washingtons vital records and other population health data. CHS provides the reliable information and statistical analysis that public health professionals, researchers, policymakers, and communities use to monitor health trends, guide public health action, and improve the health of people across Washington.

About the Washington State Department of Health

Were nearly 2,000 professionals across Washington working together to protect and improve community health. Guided by our values of Equity, Innovation, and Engagement, we address health disparities, respond to emerging challenges, and strengthen systems that support resilience. At DOH, we help reduce barriers, collaborate with diverse communities, and champion equitable health outcomes. We're passionate people who are driven to make a difference in public health. Explore more about the Department of Health, our programs, and our impact by visiting our website.

Working Conditions:

The following describes the working conditions of this position, with or without reasonable accommodation.

Work Setting:

• This positions work can be performed fully remotely. No regular in-person attendance is required. If onsite work is requested by the supervisor, the request will be planned and communicated in advance.
• 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.

Schedule:

• 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 assignment, and/or meeting business demands and deadlines. An alternative or flexible work schedule may be considered at the employees request, subject to supervisory approval.

Travel Requirements:

• Travel is not required to perform the duties of this position; however, occasional travel may be expected to attend meetings, trainings, or conferences. When driving for state business, the employee must be able to legally operate a state or privately-owned vehicle; OR provide alternate transportation while on state business.

Tools & Equipment:

• This position uses standard office furniture and equipment, such as a desk, office chair, cell phone, computer, monitor(s), keyboard, and mouse; and when in the office, the position may also require the use of a printer, phone, fax machine, and/or copy machine.
• This position requires reliable access to an internet connection sufficient to perform all job duties remotely.

Customer Interactions:

• The position regularly requires engaging with customers in a variety of settings agency staff, agency managers, agency supervisors, legislators, governors office staff, and local health jurisdictions, federal government, State Board of Health, external partners, statewide professional associations.

Other:

• This position is covered by a bargaining unit for which the Washington Federation of State Employees (WFSE) is the exclusive representative.
• The DOH campus is a smoke-free, drug-free, alcohol-free, scent-neutral environment.
• This position may be required to conduct and/or participate in public health emergency preparedness and response activities.

APPLICATION DIRECTIONS:

We're committed to a fair and equitable hiring process. Only materials submitted through the official application will be considered. Emailed resumes or documents won't be accepted or shared with the hiring manager.

Click "Apply" to complete your application. Attach your resume, cover letter, and DD-214 (if applicable). List at least three professional references, directly in your Applicant Profile or as a separate attachment, 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.

Veterans Preference: Applicants wishing to claim Veterans Preference must attach a copy of their DD-214 (Member 4 copy), NGB 22, or a signed verification of service letter from the United States Department of Veterans Affairs to their application. Please remove or cover any personally identifiable data such as social security numbers and birth year

Equity, Diversity, and Inclusion: We regard diversity as the foundation of our strength, recognizing that differing insights and abilities enable us to reflect the unique needs of the communities we serve.

DOH is an equal-opportunity employer. We prohibit discrimination based on race/ethnicity/color, creed, sex, pregnancy, age, religion, national origin, marital status, the presence or perception of a disability, veteran's status, military status, genetic information, sexual orientation, gender expression, or gender identity.

Questions and Accommodations: If you have questions, need assistance with the application process, require an accommodation, or would like to request this posting in an alternative format, please contact Shawnelle Goalder, Talent Acquisition Consultant/Recruiterat employment@doh.wa.gov and reference DOH8949 in the subject.

Technical Support: Reach out to NEOGOV directly at 1-855-524-5627 for technical support and login issues.

SUBSCRIBE to DOH Job Alerts

Supplemental Information

This recruitment may be used to fill positions of the same job classification across the agency. Once all the position(s) from the recruitment are filled, the candidate pool may be used to fill additional open positions for the next sixty (60) days.

Only applicants who follow the directions and complete the Application Process in full will have their responses reviewed for consideration.

Experience and education selected, listed, or detailed in the Supplemental Questions must be verifiable on the submitted applicant profile.

More than Just a Paycheck!

Employee benefits are not just about the kind of services you get, they are also about how much you may have to pay out of pocket. Washington State offers one of the most competitive benefits packages in the nation.

We understand that your life revolves around more than just your career. Like everyone, your first priority is ensuring that you and your family will maintain health and financial security. Thats why choice is a key component of our benefits package. We have a selection of health and retirement plans, paid leave, staff training and other compensation benefits that you can mix and match to meet your current and future needs.

Read about our benefits:

The following information describes typical benefits available for full-time employees who are expected to work more than six months. Actual benefits may vary by appointment type or be prorated for other than full-time work (e.g. part-time); view the job posting for benefits details for job types other than full-time.

Note: If the position offers benefits which differ from the following, the job posting should include the specific benefits.

Insurance Benefits

Employees and their families are covered by medical (including vision), dental and basic life insurance. There are multiple medical plans with affordable monthly premiums that offer coverage throughout the state.

Staff are eligible to enroll each year in a medical flexible spending account which enables them to use tax-deferred dollars toward their health care expenses. Employees are also covered by basic life and long-term disability insurance, with the option to purchase additional coverage amounts.

To view premium rates, coverage choice in your area and how to enroll, please visit the Public Employees Benefits Board (PEBB) website. The Washington Wellness program from the Health Care Authority works with PEBB to support our workplace wellness programs.

Dependent care assistance allows the employee to save pre-tax dollars for a child or elder care expenses.

Other insurance coverage for auto, boat, home, and renter insurance is available through payroll deduction.

The Washington State Employee Assistance Program promotes the health and well-being of employees.

Retirement and Deferred Compensation

State Employees are members of the Washington Public Employees Retirement System (PERS). New employees have the option of two employer contributed retirement programs. For additional information, check out the Department of Retirement Systems web site.

Employees also have the ability to participate in the Deferred Compensation Program (DCP). This is a supplemental retirement savings program (similar to an IRA) that allows you control over the amount of pre-tax salary dollars you defer as well as the flexibility to choose between multiple investment options.

Social Security

All state employees are covered by the federal Social Security and Medicare systems. The state and the employee pay an equal amount into the system.

Public Service Loan Forgiveness

If you are employed by a government or not-for-profit organization, and meet the qualifying criteria, you may be eligible to receive student loan forgiveness under the Public Service Loan Forgiveness Program.

Holidays

Full-time and part-time employees are entitled to paid holidays and one paid personal holiday per calendar year.

Note: Employees who are members of certain Unions may be entitled to additional personal leave day(s), please refer to position specific Collective Bargaining Agreements for more information.

Full-time employees who work full monthly schedules qualify for holiday compensation if they are employed before the holiday and are in pay status for at least 80 nonovertime hours during the month of the holiday; or for the entire work shift preceding the holiday.

Part-time employees who are in pay status during the month of the holiday qualify for the holiday on a pro-rata basis. Compensation for holidays (including personal holiday) will be proportionate to the number of hours in pay status in the month to that required for full-time employment, excluding all holiday hours. Pay status includes hours worked and time on paid leave.

Sick Leave

Full-time employees earn eight hours of sick leave per month. Overtime eligible employees who are in pay status for less than 80 hours per month, earn a monthly proportionate to the number of hours in pay status, in the month to that required for full-time employment. Overtime exempt employees who are in pay status for less than 80 hours per month do not earn a monthly accrual of sick leave.

Sick leave accruals for part-time employees will be proportionate to the number of hours in pay status, in the month to that required for full-time employment. Pay status includes hours worked, time on paid leave and paid holiday.

Vacation (Annual Leave)

Full-time employees accrue vacation leave at the rates specified in WAC 357-31-165(1) or the applicable collective bargaining agreement (CBA). Full-time employees who are in pay status for less than 80 nonovertime hours in a month do not earn a monthly accrual of vacation leave.

Part-time employees accrue vacation leave hours in accordance with WAC 357-31-165(1) or the applicable collective bargaining agreement (CBA) on a pro rata basis. Vacation leave accrual will be proportionate to the number of hours in pay status, in the month to that required for full-time employment.

Pay status includes hours worked, time on paid leave and paid holiday.

As provided in WAC 357-58-175, an employer may authorize a lump-sum accrual of vacation leave or accelerate the vacation leave accrual rate to support the recruitment and/or retention of a candidate or employee for a Washington Management Service position. Vacation leave accrual rates may only be accelerated using the rates established WAC 357-31-165.

Note: Most agencies follow the civil service rules covering leave and holidays for exempt employees even though there is no requirement for them to do so. However, agencies are required to adhere to the applicable RCWs pertaining holidays and leave.

Military Leave

Washington State supports members of the armed forces with 21 days paid military leave per year.

Bereavement Leave

Most employees whose family member or household member dies, or for loss of pregnancy, are entitled to five (5) days of paid bereavement leave. In addition, the employer may approve other available leave types for the purpose of bereavement leave.

Additional Leave

Leave Sharing

Parental Leave

Family and Medical Leave Act (FMLA)

Leave Without Pay

Please visit the State HR Website for more detailed information regarding benefits.

Updated 01-07-2026

01

Are you legally authorized to work in the United States?

• Yes
• No

02

Will you now or in the future require sponsorship for employment visa status? (e.g. H-1B, F1, TN, etc.) DOH is not an E-Verify agency]

• Yes
• No

03

I have the following qualifications (select one):

• a. 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.
• b. A bachelors 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.
• c. None of the above

04

How would you describe your experience using Python to develop or evaluate machine learning models, automate data processing, or analyze large and complex datasets?

• a. No Experience: I do not have experience using Python for machine learning, data automation, or analyzing large and complex datasets.
• b. Basic Familiarity: I have limited exposure to using Python for these purposes and have completed simple tasks or assisted others with guidance.
• c. Experienced: I have regularly used Python to develop or evaluate machine learning models, automate data processing, or analyze large and complex datasets as part of my job responsibilities.
• d. Advanced Experience: I have extensive experience using Python to develop or evaluate machine learning models, automate complex data processing, or analyze large and complex datasets, and have led projects, improved processes, or served as a technical resource in this area.

05

How would you describe your experience using SQL to extract, transform, integrate, and analyze large datasets?

• a. No Experience: I do not have experience using SQL to extract, transform, integrate, or analyze data.
• b. Basic Familiarity: I have used SQL for basic queries or simple data retrieval with guidance or limited responsibility.
• c. Experienced: I have independently used SQL to extract, transform, integrate, and analyze large datasets as a regular part of my work.
• d. Advanced Experience: I have extensive experience using SQL to manage complex data extraction, transformation, integration, and analysis, and have optimized queries, improved processes, or provided technical guidance to others.

06

How would you describe your experience developing, implementing, or evaluating machine learning or data linkage models?

• a. No Experience: I do not have experience developing, implementing, or evaluating machine learning or data linkage models.
• b. Basic Familiarity: I have limited exposure to this work and have assisted with model development, implementation, or evaluation under guidance.
• c. Experienced: I have independently developed, implemented, or evaluated machine learning or data linkage models as part of my regular job responsibilities.
• d. Advanced Experience: I have led the development, implementation, or evaluation of complex machine learning or data linkage models, improved modeling approaches, or served as a technical subject matter expert.

07

How would you describe your experience developing or maintaining automated data processing or analytical pipelines?

• a. No Experience: I do not have experience developing or maintaining automated data processing or analytical pipelines.
• b. Basic Familiarity: I have limited exposure to developing or maintaining automated pipelines and have supported routine tasks with guidance.
• c. Experienced: I have independently developed or maintained automated data processing or analytical pipelines used as part of regular business operations.
• d. Advanced Experience: I have designed, improved, or led the development of complex automated data processing or analytical pipelines and have guided others in this work.

08

How would you describe your experience evaluating data quality, validating analytical outputs, and performing quality assurance?

• a. No Experience: I do not have experience evaluating data quality, validating analytical outputs, or performing quality assurance.
• b. Basic Familiarity: I have participated in data quality reviews or validation activities with guidance or on routine assignments.
• c. Experienced: I have independently evaluated data quality, validated analytical outputs, and performed quality assurance as part of my regular responsibilities.
• d. Advanced Experience: I have established or improved quality assurance processes, resolved complex data quality issues, or provided guidance to others on data validation practices.

09

How would you describe your experience in applying statistical analysis or modeling techniques to large, complex datasets?

• a. No Experience: I do not have experience applying statistical analysis or modeling techniques to large, complex datasets.
• b. Basic Familiarity: I have applied basic statistical analysis or modeling techniques to data with guidance or on limited projects.
• c. Experienced: I have independently applied statistical analysis or modeling techniques to large, complex datasets as part of my regular work.
• d. Advanced Experience: I have applied advanced statistical analysis or modeling techniques to solve complex problems, improve analytical methods, or guide others in this work.

10

How would you describe your experience leading complex data science or analytics projects or serving as a technical subject matter expert?

• a. No Experience: I do not have experience leading complex data science or analytics projects or serving as a technical subject matter expert.
• b. Basic Familiarity: I have contributed to complex data science or analytics projects or provided technical support under the direction of others.
• c. Experienced: I have independently led data science or analytics projects or served as a technical resource within my team.
• d. Advanced Experience: I have led large or highly complex data science or analytics initiatives, served as a recognized technical subject matter expert, and guided others or influenced technical direction.

11

How would you describe your experience communicating technical findings and recommendations to technical and nontechnical audiences?

• a. No Experience: I do not have experience communicating technical findings or recommendations to technical or nontechnical audiences.
• b. Basic Familiarity: I have communicated technical information with guidance or to limited audiences.
• c. Experienced: I have regularly communicated technical findings and recommendations to both technical and nontechnical audiences and adapted my communication to meet audience needs.
• d. Advanced Experience: I have presented complex technical findings to diverse audiences, influenced decision-making, and coached or guided others in communicating technical information effectively.

12

What is the highest level of education you have completed in informatics, data science, mathematics, computer science, statistics, biostatistics, epidemiology, social science, or a related technical or quantitative field?

• a. I do not have a degree in one of these fields.
• b. I have a bachelors degree in one of these fields.
• c. I have a masters degree in one of these fields.
• d. I have a doctoral or other terminal degree in one of these fields.

13

How would you describe your experience building machine learning models using tools such as R, Python, Julia, Rust, Databricks, or similar technologies?

• a. No Experience: I do not have experience building machine learning models using these tools.
• b. Basic Familiarity: I have limited exposure to building machine learning models using one or more of these tools and have completed simple tasks or assisted others.
• c. Experienced: I have independently built machine learning models using one or more of these tools as part of my regular job responsibilities.
• d. Advanced Experience: I have extensive experience building machine learning models using one or more of these tools, have optimized or improved model performance, or have served as a technical resource for others.

14

How would you describe your experience working with large SQL-based databases?

• a. No Experience: I do not have experience working with large SQL-based databases.
• b. Basic Familiarity: I have worked with SQL-based databases on limited or routine tasks with guidance.
• c. Experienced: I have independently worked with large SQL-based databases to support regular analytical or operational work.
• d. Advanced Experience: I have managed or optimized work involving large SQL-based databases, solved complex database challenges, or provided technical guidance to others.

15

How would you describe your experience developing binary classification machine learning models, including feature engineering using raw or unstructured data?

• a. No Experience: I do not have experience developing binary classification machine learning models or performing feature engineering using raw or unstructured data.
• b. Basic Familiarity: I have limited exposure to this work and have assisted with model development or feature engineering under guidance.
• c. Experienced: I have independently developed binary classification machine learning models and performed feature engineering using raw or unstructured data as part of my regular work.
• d. Advanced Experience: I have led the development or improvement of binary classification machine learning models, applied advanced feature engineering techniques to raw or unstructured data, or guided others in this work.

16

How would you describe your experience building, maintaining, or evaluating machine learning data linkage or entity resolution projects?

• a. No Experience: I do not have experience building, maintaining, or evaluating machine learning data linkage or entity resolution projects.
• b. Basic Familiarity: I have limited exposure to this work and have supported data linkage or entity resolution projects with guidance.
• c. Experienced: I have independently built, maintained, or evaluated machine learning data linkage or entity resolution projects as part of my regular job responsibilities.
• d. Advanced Experience: I have led complex machine learning data linkage or entity resolution projects, improved methodologies or processes, or served as a technical subject matter expert in this area.

17

I have reviewed my responses to the supplemental questions for accuracy and understand they cannot be changed once the job announcement closes.

• Yes
• No

Required Question

Employer State of Washington

Address View Job Posting for Agency Information

View Job Posting for Location, Washington, 98504

Website http://www.careers.wa.gov