2

Remote Economics Data Science Jobs in Washington

Data Scientist

Alexandria, VA · On-site +1

$77K - $176K/yr

Remote Work: Hybrid Job Number: R0241357 Location: Alexandria,VA,US Share job via: Share Data Scientist The Opportunity: As a data scientist, you're excited at the prospect of unlocking the secrets ...

Data Scientist

Alexandria, VA · On-site +1

$77K - $176K/yr

Remote Work: Hybrid Job Number: R0242719 Location: Alexandria,VA,US Share job via: Share Data Scientist The Opportunity: As a data scientist, you're excited at the prospect of unlocking the secrets ...

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or ...

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or ...

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or ...

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or ...

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or ...

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or ...

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or ...

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or ...

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or ...

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or ...

Remote Hours: 40.0 Clearance: Must be eligible to obtain a US Public Trust Contact: Crystal ... Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or ...

... science, statistics, mathematics, computer science, economics, or similar). Graduate degree ... While this position is open to remote candidates across the U.S., we will prioritize those who live ...

Showing results 21-40

Remote Economics Data Science information

What are the key skills and qualifications needed to thrive as a remote economics data scientist, and why are they important?

To thrive as a Remote Economics Data Scientist, you need a strong background in economics, statistics, and data analysis, typically supported by a degree in economics, statistics, or a related field. Proficiency in programming languages like Python or R, experience with data visualization tools, and familiarity with databases or cloud platforms are essential technical skills. Strong problem-solving abilities, effective communication, and self-motivation are vital soft skills for collaborating remotely and delivering actionable insights. These skills are crucial for accurately interpreting economic data, building predictive models, and driving data-informed decision-making in a remote environment.

How do remote economics data scientists typically collaborate with cross-functional teams?

Remote Economics Data Science professionals often work closely with teams in product, engineering, and business strategy through virtual meetings, shared dashboards, and collaborative tools. Communication is key, as they translate complex economic models and data findings into actionable insights for stakeholders with varying technical backgrounds. Regular check-ins, clear documentation, and participation in agile sprints or project cycles help align goals and ensure that data-driven recommendations are integrated into decision-making processes. Adapting to different time zones and building strong virtual relationships are important aspects of effective collaboration in this remote role.

What is a remote economics data scientist?

A Remote Economics Data Scientist is a professional who analyzes large sets of economic and financial data to extract insights, build predictive models, and support decision-making, all while working from a remote location. They combine expertise in economics, statistics, programming, and data analysis to interpret trends and inform business or policy strategies. Remote Economics Data Scientists often use tools such as Python, R, SQL, and data visualization platforms to communicate findings effectively. Their work can span industries like finance, government, consulting, and academia.
What are popular job titles related to Remote Economics Data Science jobs in Washington? For Remote Economics Data Science jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Remote Economics Data Science jobs in Washington look for? The top searched job categories for Remote Economics Data Science jobs in Washington are:
What cities in Washington are hiring for Remote Economics Data Science jobs? Cities in Washington with the most Remote Economics Data Science job openings:

Data Scientist (Remote Eligible)

Mathematica

Washington, DC • On-site, Remote

Full-time

Re-posted yesterday


Job description

Mathematica applies expertise at the intersection of data, methods,policy, and practice to improve well-being around the world. We collaborateclosely with public- and private-sector partners to translate big questionsinto deep insights that improve programs, refine strategies, and enhanceunderstanding. Our work yields actionable information to guide decisions inwide-ranging policy areas, from health, education, early childhood, and familysupport to nutrition, employment, disability, and international development. Mathematicaoffers our employees competitive salaries, and a comprehensive benefitspackage, as well as the advantages of being 100 percent employee owned. As anemployee stock owner, you will experience financial benefits of ESOP holdingsthat have increased in tandem with the company's growth and financial strength.You will also be part of an independent, employee-owned firm that is able todefine and further our mission, enhance our quality and accountability, andsteadily grow our financial strength. Learn more about our benefits here.
AtMathematica, we take pride in our commitment to diversity. Building aninclusive culture that draws on the individual strengths of employees fromdifferent ethnic backgrounds, cultures, lifestyles, abilities, and experienceis key to our success.
We arelooking for a Data Scientist who will derive meaning from data throughthe creation and deployment of data-driven approaches to solve problems andanswer important policy questions for clients. A Data Scientist owns dataprocessing and analysis tasks and supports more senior level data science staffin implementing statistical, machine learning, generative AI, and other datascience methods for use in research reports, internal systems, or clientsystems. Data Scientists will work on all aspects of the data science project lifecycle, including understanding client needs, building data pipelines,monitoring data quality, developing documentation, creating visualizations,brainstorming modeling approaches, and implementing those models. Our datascientists underpin our company's core offerings in program improvement, policyassessment, and data science, which yield crucial evidence and information forpolicy and decision makers.  Thisposition will work remotely or flexibly in one of our office locations.
Exampleprojects include:

  • Build and evaluate generative AI tools to extract clinically important information from unstructured doctors' notes, then use that information to construct predictive models and descriptive statistics to improve doctor decision-making and predictive accuracy.
  • Evaluate and monitor the impacts of an alternative payment model for primary care in terms of care quality, cost, and health outcomes for diverse beneficiaries, using claims from thousands of primary care practices across the country. Use the same data to predict future hospital costs and behavior.
  • Analyze nationwide geographic access to food retailers by integrating geospatial data on retailer locations, neighborhood demographics, demand, and social vulnerability. Apply network-based accessibility analyses to compare convenient access within and across states overall and by urbanicity and retailer type and develop interactive dashboards that help policymakers identify disparities and improve access to nutrition assistance.
  • Use national survey data and grocery store purchase data to simulate realistic American diets and analyze their nutritional value. Analyze how that nutritional value compares to guidelines and what it suggests are practical, culturally aware food baskets consumers might purchase to meet the guidelines.
  • Build knowledge synthesis solutions for government and foundation clients leveraging NLP and GenAI methods (knowledge graphs, Model Context Protocol, retrieval-augmented generation) to extract quantitative information (e.g., summary statistics, regression results) and contextual details (e.g., implementation specifics, focus group discussion themes) to distill large literatures into digestible datasets that support evidence-informed policymaking.
  • Develop and evaluate a reproducible benchmarking pipeline to compare state healthcare spending against peer markets nationwide, harmonizing multi-source claims and Census data, applying statistical matching to select comparable regions, and normalizing spending through risk-adjusted regression models to support state rate-setting decisions.
  • Build and evaluate interpretable machine learning models to predict clinical care tiers from health assessment data, supporting state healthcare program's transition to a new assessment tool.
  • Partner with subject-matter experts to engineer clinically meaningful features from raw assessment items, and apply stratified sampling and diagnostics to deliver transparent models suited to high-stakes eligibility and reimbursement decisions.

Specifically,this Data Scientist contributes to team-based projects by:

  • Conducting causal, predictive, and descriptive analyses
  • Writing and maintaining programming systems in languages such as Python and R to build and evaluate models
  • Developing reliable data pipelines to obtain, combine, and transform datasets on cloud, internal, and client servers
  • Communicating technical results to diverse stakeholders including clients and cross-functional teams
  • Developing and maintaining technical and methodological documentation
  • Co-developing analysis plans with a senior data scientist or researcher
  • Leading and managing small teams and tasks with oversight from a more senior staff member