Data Analyst (Temporary)

University of Washington; Seattle (WA); On-site; USD 78,000 - 90,000; Full time

Job summary

The Institute for Health Metrics and Evaluation (IHME) at the University of Washington is seeking a Temporary Data Analyst to turn complex health data into actionable insights and support publications across multidisciplinary research projects.

Responsibilities include collaborating with researchers, preparing data pipelines in Python, and maintaining reproducible analyses. Requires a bachelor's degree with related experience and strong English communication.

Qualifications

• Bachelor’s degree in social sciences, engineering, computer science, or related field plus two years’ related experience.
• Proficiency with Python (pandas, NumPy) for data analysis tasks including cleaning, transformation, visualization, and statistical evaluation.
• Ability to evaluate and integrate emerging technologies into data workflows to improve scalability, accuracy, and reproducibility of analyses.
• Interest in global health, population health, and how quantitative research and data science create valuable global public goods.
• Experience working with large secondary datasets.
• Strong written and spoken English communication.
• Demonstrated self-motivation, attention to detail, flexibility, and ability to thrive in a fast-paced, creative, entrepreneurial environment.
• Ability to learn new information quickly and apply analytic skills to understand complex information systematically.
• Strong quantitative aptitude
• Flexible attitude and willingness to move between different research teams to gain broader experience.

Responsibilities

• Familiarize with substantive areas of expertise to understand health data dimensions and the analytic foundations of various research streams.
• Collaborate with researchers to locate data sources used in models and results, grasp data context, and ensure relevance to analyses.
• Create and document efficient, replicable methods for data extraction, code development, data source organization, data quality management, and explanation of analytic processes.
• Follow protocols to identify dataset or process problems, rectify issues, and systematize data for future analyses.
• Transform and format datasets for ongoing analyses; perform quality checks; standardize inputs from surveys, vital registration systems, administrative records, and scientific literature.
• Resolve computational and analytic challenges by exploring the data, clarifying questions, and proposing alternative measurement strategies.
• Execute code solutions to address analytic questions, diagnose results, and test and evaluate new methods.
• Maintain, update, and execute routine yet complex computational processes and statistical modeling central to estimating key indicators.
• Maintain reproducible analytic pipelines in Python with Git version control.
• Address intricate questions to support senior researchers and external requests from collaborators, media, policymakers, donors, and other stakeholders.
• Leverage emerging technologies to optimize data workflows, enhance analysis and visualization, and assist with routine data quality checks and issue identification.

Skills

Python

Data analysis

English communication

Quantitative aptitude

Learning agility

Education

Bachelor’s degree in social sciences, engineering, computer science, or related field

Tools

Git

Linux compute clusters

Pandas

NumPy

Job description

Temporary Data Analyst role with the Institute for Health Metrics and Evaluation at the University of Washington, focused on turning complex health data into actionable insights and supporting publications across multidisciplinary research projects.

Responsibilities

• Familiarize with substantive areas of expertise to understand health data dimensions and the analytic foundations of various research streams
• Collaborate with researchers to locate data sources used in models and results, grasp data context, and ensure relevance to analyses
• Create and document efficient, replicable methods for data extraction, code development, data source organization, data quality management, and explanation of analytic processes
• Follow protocols to identify dataset or process problems, rectify issues, and systematize data for future analyses
• Transform and format datasets for ongoing analyses; perform quality checks; standardize inputs from surveys, vital registration systems, administrative records, and scientific literature
• Resolve computational and analytic challenges by exploring the data, clarifying questions, and proposing alternative measurement strategies
• Execute code solutions to address analytic questions, diagnose results, and test and evaluate new methods
• Maintain, update, and execute routine yet complex computational processes and statistical modeling central to estimating key indicators
• Maintain reproducible analytic pipelines in Python with Git version control
• Address intricate questions to support senior researchers and external requests from collaborators, media, policymakers, donors, and other stakeholders
• Leverage emerging technologies to optimize data workflows, enhance analysis and visualization, and assist with routine data quality checks and issue identification

Requirements

• Bachelor’s degree in social sciences, engineering, computer science, or related field plus two years’ related experience
• Proficiency with Python (pandas, NumPy) for data analysis tasks including cleaning, transformation, visualization, and statistical evaluation
• Ability to evaluate and integrate emerging technologies into data workflows to improve scalability, accuracy, and reproducibility of analyses
• Interest in global health, population health, and how quantitative research and data science create valuable global public goods
• Experience working with large secondary datasets
• Strong written and spoken English communication
• Demonstrated self-motivation, attention to detail, flexibility, and ability to thrive in a fast-paced, creative, entrepreneurial environment
• Ability to learn new information quickly and apply analytic skills to understand complex information systematically
• Strong quantitative aptitude
• Flexible attitude and willingness to move between different research teams to gain broader experience

Technologies

• Python
• pandas
• NumPy
• Git
• Linux compute clusters

About the IHME team

The Institute for Health Metrics and Evaluation is an independent research organization within the University of Washington. Its mission is to deliver timely, relevant, and scientifically valid evidence to improve health policy and practice, helping people live longer, healthier lives. IHME conducts projects across areas such as Global Burden of Diseases, Injuries, and Risk Factors and Future Health Scenarios.

Compensation, Benefits and Position Details

• Pay range: Minimum $78,324.00 annually; Maximum $90,072.00 annually
• Benefits: For information about benefits for this position, visit https://www.washington.edu/jobs/benefits-for-temporary-per-diem-and-less-than-half-time/
• Shift: First Shift (United States of America)
• Temporary or Regular: This is a temporary position
• FTE: 100.00%
• Union/Bargaining Unit: SEIU Local 925 - IHME

About the University of Washington

Working at the University of Washington provides a unique opportunity to impact lives on campus, in our state, and around the world.

Our Commitment

The University of Washington is committed to fostering an inclusive, respectful, and welcoming community for all. As an equal opportunity employer, UW considers applicants without regard to race, color, creed, religion, national origin, citizenship, sex, pregnancy, age, marital status, sexual orientation, gender identity or expression, genetic information, disability, or veteran status in line with UW policy.