Note: The job is a remote job and is open to candidates in USA. The University of Washington is seeking a Data Analyst to join the Simulation Science team at the Institute for Health Metrics and Evaluation (IHME). The Data Analyst will be responsible for managing large datasets, ensuring data quality, and providing computational support to turn complex health data into actionable insights for research projects.
Responsibilities
- Become familiar with substantive areas of expertise to understand the dimensions and uses of health data and the analytic underpinnings of different research streams
- Work directly with researchers to identify the source of data used in models and results, understand the context of the data, and ensure that they are relevant to the analyses themselves
- Create and document efficient, effective, and replicable methods for extracting data, developing code, organizing data sources, managing data quality, and explaining complex analytic processes
- Use protocols to identify problems with datasets and routine computational processes, rectify issues, and systematize data for future analyses
- Transform and format datasets for use in ongoing analyses; perform quality checks. Transform and standardize datasets from a wide range of inputs such as surveys, vital registration systems, administrative records, and scientific literature
- Problem-solve computational and analytic challenges by investigating the data, understanding the root questions, and coming up with alternative measurement strategies
- Execute code solutions in order to answer analytic questions, perform diagnostics on results, and test and assess new methods
- Maintain, update, and carry out routine but complex computational processes and statistical modeling that are central to generating estimates of key indicators
- Maintain reproducible analytic pipelines in Python, version-controlled in Git
- Resolve intricate questions in order to respond to the needs of senior researchers and external requests from collaborators, media, policymakers, donors, and other stakeholders
- Use emerging technologies to optimize data workflows, enhance analysis and visualization, and assist with routine data quality checks and issue identification
- Create tables, figures, and charts for concept notes, presentations, publications, and proposals
- Provide referencing and other support for publications and presentations
- Communicate clearly and effectively while contributing as a member of the Institute
- Work closely with other team members to assist with relevant tasks, facilitate learning new skills, and help resolve emerging problems on different projects
- Other duties as assigned
Skills
- Bachelor's degree in social sciences, engineering, computer science, or related field plus two years' related experience
- Proven experience and proficiency in using Python (pandas, NumPy) for data analysis tasks, including, but not limited to, data cleaning, transformation, visualization, and statistical evaluation
- Demonstrated 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/or ways in which quantitative research and data science can be used to create valuable global public goods
- Experience working with large secondary datasets
- Strong written and spoken communication in English
- Demonstrated self-motivation, ability to absorb detailed information, flexibility, and ability to thrive in a fast-paced, energetic, highly creative, and entrepreneurial environment
- Ability to learn new information quickly and apply analytic skills to better understand complex information in a systematic way
- Strong quantitative aptitude
- Flexible attitude and interest in moving around to a variety of different research teams, getting a broader range of experience, rather than focusing on a particular research area or team
- Master's degree in a relevant quantitative discipline
- Experience with household survey data (DHS, MICS, LSMS, or similar)
- Familiarity with simulation modeling, microsimulation, or agent-based modeling
- Experience with Linux compute clusters
- Working knowledge of Git and collaborative software development practices
- Prior public-health or nutrition research experience
Benefits
- For information about benefits for this position, visit https://www.washington.edu/jobs/benefits-for-temporary-per-diem-and-less-than-half-time/
Company Overview