3

Data Science Entry Level Remote Jobs in Washington

Data Scientist

Alexandria, VA ยท On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0242764 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 held ...

Data Scientist

Mclean, VA ยท On-site +1

$99K - $225K/yr

Remote Work: No Job Number: R0236797 Location: McLean,VA,US Share job via: Share Data Scientist The Opportunity: As a data scientist, you're excited at the prospect of unlocking the secrets held by a ...

Data Scientist, Mid

Arlington, VA ยท On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0239482 Location: Arlington,VA,US Share job via: Share Data Scientist, Mid The Opportunity: Are you excited at the prospect of unlocking the secrets held by a data set?

Data Scientist

Alexandria, VA ยท On-site +1

$77K - $176K/yr

Remote Work: Hybrid Job Number: R0241528 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

Chantilly, VA ยท On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0244172 Location: Chantilly,VA,US Share job via: Share Data Scientist The Opportunity: As a data scientist, you're excited at the prospect of unlocking the secrets held ...

Data Scientist, Mid

Arlington, VA ยท On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0241792 Location: Arlington,VA,US Share job via: Share Data Scientist, Mid The Opportunity: As a data scientist, you're excited at the prospect of unlocking the secrets ...

Data Scientist, Mid

Arlington, VA ยท On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0239679 Location: Arlington,VA,US Share job via: Share Data Scientist, Mid The Opportunity: As a data scientist, you're excited at the prospect of unlocking the secrets ...

Data Scientist, Mid

Arlington, VA ยท On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0243983 Location: Arlington,VA,US Share job via: Share Data Scientist, Mid The Opportunity: As a data scientist, you're excited at the prospect of unlocking the secrets ...

This is a Remote position. Key Responsibilities * Data Collection and Preprocessing: * Develop ... Integrate data science workflows with existing systems and applications to enable seamless data ...

This is a Remote position. Key Responsibilities * Data Collection and Preprocessing: * Develop ... Integrate data science workflows with existing systems and applications to enable seamless data ...

Data Scientist

Chantilly, VA ยท On-site +1

$62K - $141K/yr

Remote Work: No Job Number: R0243682 Location: Chantilly,VA,US Share job via: Share Data Scientist The Opportunity: As a data scientist, you're excited at the prospect of unlocking the secrets held ...

next page

Showing results 1-20

Data Science Entry Level Remote information

What are some typical challenges entry-level data scientists face when working remotely, and how can they overcome them?

Entry-level data scientists working remotely often encounter challenges such as limited access to mentorship, difficulty in collaborating on complex projects, and adjusting to asynchronous communication. To overcome these, it's important to proactively seek guidance from senior team members through regular check-ins, participate actively in team meetings and online forums, and document your work thoroughly for transparency. Leveraging collaborative tools like shared code repositories and communication platforms can also help maintain strong connections with your team and ensure project alignment.

What are the key skills and qualifications needed to thrive as an entry-level remote Data Scientist, and why are they important?

To thrive as an entry-level remote Data Scientist, you need a solid background in statistics, programming (often Python or R), and data analysis, typically supported by a relevant degree or certification. Familiarity with tools like Jupyter Notebook, SQL databases, and machine learning libraries such as scikit-learn or TensorFlow is commonly required. Strong problem-solving abilities, communication skills, and self-motivation are crucial soft skills for remote collaboration and project management. These competencies enable effective data-driven insights, seamless teamwork, and measurable contributions in a distributed work environment.

What is the difference between Data Science Entry Level Remote vs Data Analyst Entry Level Remote?

AspectData Science Entry Level RemoteData Analyst Entry Level Remote
Required CredentialsBachelor's in CS, Statistics, or related field; some knowledge of programming and machine learningBachelor's in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentRemote, collaborative teams, often with cross-functional departmentsRemote, often working independently or with business teams
Employer & Industry UsageTech companies, finance, healthcare, e-commerceBusiness, marketing, finance, healthcare

While both roles are entry-level remote positions involving data, Data Science Entry Level Remote focuses on programming, machine learning, and predictive modeling, whereas Data Analyst Entry Level Remote emphasizes data visualization, reporting, and interpreting data for business insights. Candidates should choose based on their skills and career interests.

What are data science entry level remote jobs?

Data science entry level remote jobs are positions suitable for individuals who are just starting their careers in data science and prefer or require the flexibility to work from home or any location outside the traditional office setting. These roles typically involve tasks such as data cleaning, basic statistical analysis, creating simple data visualizations, and assisting with machine learning projects under supervision. Entry level data scientists often work closely with more experienced team members and use tools like Python, R, SQL, and Excel. Remote roles require good communication skills and self-motivation, as collaboration happens online. These positions are a great way to gain practical experience and develop technical skills in the field of data science.
What are the most commonly searched types of Data Science Remote jobs in Washington? The most popular types of Data Science Remote jobs in Washington are:
What are popular job titles related to Data Science Entry Level Remote jobs in Washington? For Data Science Entry Level Remote jobs in Washington, the most frequently searched job titles are:
What cities in Washington are hiring for Data Science Entry Level Remote jobs? Cities in Washington with the most Data Science Entry Level Remote job openings:
Infographic showing various Data Science Entry Level Remote job openings in Washington as of July 2026, with employment types broken down into 8% Internship, 68% Full Time, 15% Part Time, 4% Temporary, and 5% Contract. Highlights an 100% Remote job distribution.
Data Scientist (Remote Eligible)

Data Scientist (Remote Eligible)

Mathematica

Washington, DC โ€ข On-site, Remote

Other

Posted 12 days ago


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. ย 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