Data Analyst (Temporary), Simulation Science

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 exciting opportunity for a Data Analyst on the Simulation Science team.

The Simulation Science team models the impact and cost-effectiveness of health care interventions for a variety of stakeholders. The scope of our work is wide. We produce models to compare interventions on maternal and child health, to evaluate new drugs for the treatment of non-communicable diseases, and to gauge the impact of public policy interventions on disease dynamics. This modeling work is done using a flexible, open-source simulation framework run on IHME’s 20,000-core high-performance computing cluster.

The main purpose of the Data Analyst position is to provide support to key research projects through database management, data quality management, computational support to multidisciplinary research projects, data extraction and formatting, and providing key inputs for papers and presentations. Data Analysts must develop an understanding of different research needs and analytic functions across multiple projects to best meet research needs. Data Analysts must be able to independently translate requests into actionable results through interactions with research databases, formulation of displays of results, and development of complex code to be applied to a variety of quantitative data.

This position calls for dexterity working with complex databases and the ability to assess, transform, and utilize quantitative data using multiple coding languages (Python, R, SQL, Stata). The individual must then quality control results to ensure that other team members have exactly what they need to incorporate the data and results into their own components of the analytic process, presentations, and papers. Additionally, this position will work alongside other Data Analysts on complementary projects and will require knowledge and skill sharing and collective problem solving. Overall, the Data Analyst will be a critical member of an agile, dynamic team. IHME is a grant funded organization and this position is contingent on project funding availability.

Responsibilities:

Research command

• 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.

Data management and analytics

• 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.

• Resolve intricate questions in order to respond to the needs of senior researchers and external requests from collaborators, media, policymakers, donors, and other stakeholders.

General

• Create tables, figures, and charts for presentations and publications.

• 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.

• Participate in overall community of the Institute, carrying out duties as assigned as team members with other Institute members.

Minimum Qualifications:

• Bachelor's degree in social sciences, engineering, computer science, or related field plus two years' related experience, or equivalent combination of education and experience.

Additional Qualifications:

• Demonstrated success in developing code in Python or R.

• 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.

• 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.

• A commitment to working alongside other at IHME to illuminate the health impact of systemic racism and to work within IHME to make out organization more diverse and inclusive. See IHME's DEI statement here: https://www.healthdata.org/about/dei.

Desirable Qualifications:

• Demonstrated ability in using databases with large-scale, complex datasets.

• Shown interest in data seeking in scientific literature such as conducting comprehensive searches or running meta-analyses based on multiple sources.

• Experience in scientific writing such as documentation of data processes or writing for scientific publication.

• Knowledge of with Python packages such as Pandas, NumPy, Matplotlib and/or Seaborn, and experience with interfaces including VS Code or Jupyter notebook.

Conditions of Employment:

• Weekend and evening work 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.

• 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.