RESEARCH SCIENTIST (Project/Temporary)

University of Washington; Seattle (WA); Remote; USD 150,000 - 200,000; Full time

Job summary

The University of Washington seeks a Research Scientist for a project focusing on the effects of lead exposure on cardiovascular disease. This temporary role requires advanced statistical and epidemiological expertise, with responsibilities including data analysis and model development. Join a dynamic team dedicated to improving global health outcomes through innovative research.

Benefits

Generous benefits

Professional growth opportunities

Inclusive and equitable work environment

Qualifications

• Master's degree in public health, life sciences, or related fields plus four years' experience.
• Advanced skills in statistical analysis and epidemiological modelling.
• Strong peer-reviewed publication record.

Responsibilities

• Design, analyze, and interpret complex epidemiologic models.
• Conduct quantitative analyses to inform health policies.
• Mentor junior staff and contribute to peer-reviewed publications.

Skills

Biostatistics

Epidemiological methods

Quantitative data analysis

Statistical modelling

Machine learning

Education

Master’s degree in public health or related field

Tools

R

Job description

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Req #: 247106

Department: INSTITUTE FOR HEALTH METRICS AND EVALUATION (IHME)

Appointing Department Web Address: http://healthdata.org

Job Location Detail: The IHME office is located in Seattle, Washington. This position is eligible to work fully remote in the US excluding US territories

Posting Date: 06/18/2025

Closing Info: Closes On 07/04/2025

Salary: $9,443 - $10,024 per month

Shift: First Shift

Notes: As a UW employee, you will enjoy generous benefits and work/life programs. For a complete description of our benefits for this position, please visit our website, click here. (https://hr.uw.edu/benefits/wp-content/uploads/sites/3/2018/02/benefits-professional-staff-librarians-academic-contract-covered-exempt-20250130-a11y.pdf)

As a UW employee, you have a unique opportunity to change lives on our campuses, in our state and around the world. UW employees offer their boundless energy, creative problem-solving skills, and dedication to build stronger minds and a healthier world.

UW faculty and staff also enjoy outstanding benefits, professional growth opportunities and unique resources in an environment noted for diversity, intellectual excitement, artistic pursuits, and natural beauty.


The Institute for Health Metrics and Evaluation (IHME)

is an independent research organization at the University of Washington (UW). Its mission is to deliver to the world timely, relevant, and scientifically valid evidence to improve health policy and practice. IHME carries out its mission through a range of projects within different research areas including the Global Burden of Diseases (GBD), Injuries, and Risk Factors; Future Health Scenarios; Cost Effectiveness and Efficiency; Resource Tracking; and Impact Evaluations.

IHME is committed to providing the evidence base necessary to help solve the world’s most important health problems. This requires creativity and innovation, which are cultivated by an inclusive, diverse, and equitable environment that respects and appreciates differences, embraces collaboration, and invites the voices of all IHME team members.


IHME has an outstanding opportunity for a

Temporary

Research Scientist (IHME Research Scientist 2)

with the

Program in Cardiovascular Health Metrics (PCHM)

in collaboration with the Environmental Risk Factors Team.

The PCHM at UW is dedicated to improving heart and vascular health and health care around the world. The Program represents an innovative collaboration between IHME and the UW Medicine Division of Cardiology.

This position will contribute to work conducted by the PCHM and the Environmental and Occupational Risk Factors team at IHME, composed of faculty, researchers, data professionals, and project managers. These teams possess expertise in linking lead exposure to health outcomes, an advanced understanding of cardiovascular disease (CVD) and associated pathophysiologic mechanisms, and technical skills encompassing the data management, coding, and statistical methods required for the proposed work, including causal inference and relative risk analyses.

We are seeking an experienced and motivated

Research Scientist

to contribute to an innovative global health project focused on the impact of lead exposure on cardiovascular disease (CVD) outcomes. This research aims to strengthen the evidence on global health risks associated with lead exposure and use this data to inform actionable health policies.

As a

Research Scientist

, you will play an integral role in identifying and analyzing data from cohort studies that measure lead exposure via bone and blood lead levels, as well as assessing the relationship between lead exposure and various CVD outcomes. You will be directly involved in designing, analyzing, and interpreting complex epidemiologic models to address critical policy-relevant questions. Your role will involve leveraging demographic and epidemiologic modelling methods, applying deep learning techniques to large datasets, and collaborating with clinical experts to improve our understanding of lead-related health risks. You will be responsible for contributing to model development, leading the creation of relative risk curves, and assessing statistical methods to ensure the robustness and accuracy of our findings. Additionally, you will collaborate closely with a team of researchers from diverse subject areas, mentoring junior staff, and guiding the research process to ensure that project milestones are met in a timely and efficient manner. You will also contribute to the dissemination of research findings through peer-reviewed publications and other means, building a strong portfolio of scientific work.

You should have advanced experience in epidemiological and demographic modelling, statistical analysis, and machine learning methods. You thrive in a collaborative, dynamic environment and are capable of managing multiple projects while meeting deadlines. If you are excited about advancing the science of lead exposure and cardiovascular disease, and are eager to make a global impact on health policy, we encourage you to apply.

IHME is a grant-funded organization, and this position is contingent on project funding availability. The expected funding for this position is 24 months.


Responsibilities:

• Advanced skills in designing, executing, and troubleshooting code in R. Maintain, modify, and execute analytic machinery that generates results.
• Independently carry out quantitative analyses and participate in reciprocal research projects. Interpret and vet results from junior staff, formulate conclusions, and inform team leaders.
• Conducting a comprehensive search for relevant data sources to expand the research database and improve estimates.
• Leading the analysis of cohort studies and other relevant data sources on lead exposure and cardiovascular outcomes.
• Develop, quality check, and distribute complex datasets to be used in epidemiological and statistical analyses.
• Developing and refining statistical models to quantify the association between blood and bone lead levels with specific cardiovascular diseases.
• Applying advanced machine learning methods, including deep learning and survival analysis techniques, to enhance model precision and predictability.
• Leading the creation of relative risk curves and conducting rigorous cross-validation to select the best models for lead-related health outcomes.
• Contributing to presentations, the publication of research findings, and the development of actionable policy recommendations.
• Engaging in regular communication with team members and external partners to align on research goals and deliverables.
• Managing key aspects of project workflow, including tracking milestones, ensuring deadlines are met, and reporting progress internally and externally.
• Leading and mentoring junior staff.
• Other duties as assigned that fall within reasonable scope of the research program.
  
  
  
  

Minimum Qualifications:

• Master’s degree in public health, life sciences, epidemiology, statistics, biostatistics, quantitative social sciences, or related discipline plus four years' related experience, or equivalent combination of education and experience.
  
  

Additional Qualifications:

• Advanced skills in biostatistics, and epidemiological methods.
• Advanced coding and quantitative data analysis using R.
• Strong peer-reviewed publication record.
• Content knowledge related to cardiovascular or environmental health as demonstrated by educational experience, peer reviewed papers, or other disseminated work.
• Solid command of quantitative areas, a given disease, risk, key indicator, relevant methodological area, and the related data sources and scientific underpinnings.
• Excellent analytic, critical thinking, and quantitative skills.
• Results- and detail-oriented individual who can initiate and complete tasks under tight deadlines and changing priorities both independently and in a team environment.
• Experience devising and executing statistical modelling techniques.
• Demonstrated ability to quickly recognize problems in results and identify root causes in data, methods, and code.
• Excellent written and oral communication skills required, including track record of success in co-authorship on multiple scientific papers, presenting results, and representing research at meetings.
• Demonstrated ability to contribute to and sustain collaborations with external research teams.
• Ability to work both independently and in collaboration with a team.
• A commitment to working alongside others at IHME to illuminate the health impacts of systemic racism and to work within IHME to make our organization more diverse and inclusive. See IHME’s DEI statement here: https://www.healthdata.org/about/dei .
  
  
  
  

Desirable Qualifications:

• Doctoral degree in public health, life sciences, epidemiology, statistics, biostatistics, or quantitative social sciences, plus two years’ experience preferred.
• Experience with machine learning, data mining, and analytic techniques.
• Experience mentoring and developing junior employees on soft and technical skills.
• Experience with project management methods.
• Evidence of translating research into policy.
  
  
  
  

Conditions of Employment:

• Weekend and evening work are sometimes required.
• This position is open to anyone authorized to work in the US.
• Working internationally is only allowed for IHME sponsored work that requires in-country participation.
• The IHME office is located in Seattle, Washington. This position is eligible to work fully remote in the US; work schedule required to overlap 50% of IHME office hours, between 8 a.m. and 6 p.m. Pacific Time as agreed upon between employee and supervisor.
  
  

Committed to attracting and retaining a diverse staff, the University of Washington will honor your experiences, perspectives and unique identity. Together, our community strives to create and maintain working and learning environments that are inclusive, equitable and welcoming.

Application Process:


The application process for UW positions may include completion of a variety of online assessments to obtain additional information that will be used in the evaluation process. These assessments may include Work Authorization, Cover Letter, and/or others. Any assessments that you need to complete will appear on your screen as soon as you select “Apply to this position”. Once you begin an assessment, it must be completed at that time; if you do not complete the assessment you will be prompted to do so the next time you access your “My Jobs” page. If you select to take it later, it will appear on your "My Jobs" page to take when you are ready.

Please note that your application will not be reviewed, and you will not be considered for this position until all required assessments have been completed.


University of Washington is an affirmative action and equal opportunity employer. All qualified applicants will receive consideration for employment without regard to, among other things, race, religion, color, national origin, sexual orientation, gender identity, sex, age, protected veteran or disabled status, or genetic information.

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