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Weekend Remote Data Scientist Jobs in Reston, VA

Data Scientist

Mclean, VA · On-site +1

$200K - $240K/yr

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a Data Scientist to join our team to provide support specializing in natural language(NLP) processing and associated data ...

Data Scientist

Mclean, VA · On-site +1

$200K - $240K/yr

None Potential for Remote Work: ORA_ON_SITE Description SAIC is seeking a Data Scientist to join our team to provide Subject Matter expertise and support specializing in natural language(NLP ...

Using your skills as a Data Scientist , you will organize and interpret data to inform U.S ... This position has an on-site requirement and is not eligible for fully remote candidates. At Level ...

We're looking for an experienced Data Scientist or Senior Data Scientist to join one of our cross-functional product development teams here at Two Six Technologies. Our teams are building ...

Responsibilities Using your skills as a Data Scientist , you will organize and interpret data to ... This position has an on-site requirement and is not eligible for fully remote candidates. At Level ...

Applied Data Scientist

Arlington, VA · On-site +1

$120K - $170K/yr

Shift5 is seeking an Applied Data Scientist to join our growing Data Science team. In this role ... Flexible work & remote work policy  * Tax-deferred public transit benefits with Metro ...

Data Scientist TS/SCI (DC/NoVA) Virtualitics introduced Intelligent Exploration to the analytics community through the Virtualitics AI Platform. We are seeking a Data Scientist with TS/SCI security ...

... remote work) and requires a TS/SCI + Poly clearance (acceptable to this customer). What You'll be ... This role, requires working with a team of developers, data scientists, SMEs, and cyber analysts to ...

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $220K/yr

We are seeking a Senior Data Scientist to develop machine learning models, predictive analytics ... Local and remote candidates (living within Eastern or Central Time Zone) will be considered. No ...

The BlueLabs Data Science Team develops deep expertise and uses data to inform strategic advice to our clients. Our polling work designs, implements, and fields tools that power our analysis and ...

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $220K/yr

We are seeking a Senior Data Scientist to develop machine learning models, predictive analytics ... Local and remote candidates (living within Eastern or Central Time Zone) will be considered. No ...

Location Fully remote within the USA, with travel once or twice a year for retreats and conferences ... of Data Science (45 minutes) 3. Data Case - to be completed the week of final interview and ...

We are seeking an experienced Data Scientist to deliver critical insights to our customer, TacSRT ... Our team member must be willing to be on call for weekend requirements. The candidate MUST be a US ...

... remote work) and requires a TS/SCI + Poly clearance (acceptable to this customer). What You'll be ... This role, requires working with a team of developers, data scientists, SMEs, and cyber analysts to ...

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Showing results 1-20

Weekend Remote Data Scientist information

See Reston, VA salary details

$39K

$127.7K

$204.4K

How much do weekend remote data scientist jobs pay per year?

As of Jul 13, 2026, the average yearly pay for weekend remote data scientist in Reston, VA is $127,692.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,500.00 and $141,500.00 per year, depending on experience, location, and employer.

What is the difference between Weekend Remote Data Scientist vs Part-Time Data Analyst?

AspectWeekend Remote Data ScientistPart-Time Data Analyst
CredentialsBachelor's or Master's in Data Science, Statistics, or related fieldBachelor's degree in related field, often with similar certifications
Work EnvironmentRemote, flexible hours, project-basedRemote or on-site, flexible hours, project or hourly-based
Industry UsageTech, finance, healthcare, e-commerceBusiness, marketing, research, finance
Search & Comparison IntentFocus on data science skills, modeling, machine learningFocus on data analysis, reporting, visualization

The Weekend Remote Data Scientist typically works on complex data modeling and machine learning projects during weekends, requiring advanced data science skills. In contrast, a Part-Time Data Analyst focuses on data reporting, visualization, and basic analysis, often during flexible hours. Both roles are remote and part-time but differ in technical complexity and daily responsibilities.

What are Weekend Remote Data Scientists?

Weekend Remote Data Scientists are professionals who work part-time or on a flexible schedule, typically during weekends, to analyze data, build models, and generate insights for organizations. They perform their duties remotely, using data science tools and techniques to solve business problems without needing to be physically present at an office. This role is ideal for those seeking work-life balance, additional income, or flexibility in their work schedule. Weekend Remote Data Scientists often collaborate with teams via virtual communication platforms and use cloud-based tools to access and analyze data securely.

What are the key skills and qualifications needed to thrive as a Weekend Remote Data Scientist, and why are they important?

To thrive as a Weekend Remote Data Scientist, you need strong analytical skills, expertise in statistics, and a background in computer science or mathematics, often supported by a relevant degree. Familiarity with programming languages such as Python or R, experience with machine learning libraries, and knowledge of data visualization tools and cloud platforms are typically expected. Excellent time management, self-motivation, and clear communication skills are essential for independent remote work and effective collaboration with distributed teams. These skills ensure accurate data-driven insights, efficient project delivery, and seamless coordination in a remote and flexible work environment.

What are some common challenges faced by weekend remote data scientists, and how can they be addressed?

Weekend remote data scientists often face challenges such as managing communication with teammates who work standard weekday hours and accessing time-sensitive data or support outside regular business times. To overcome these hurdles, it's important to set clear expectations with your team, utilize asynchronous communication tools (like Slack or email), and plan your tasks in advance to ensure you have all necessary resources before the weekend. Proactively updating your team on progress and any blockers can also help maintain collaboration and project momentum.
What are popular job titles related to Weekend Remote Data Scientist jobs in Reston, VA? For Weekend Remote Data Scientist jobs in Reston, VA, the most frequently searched job titles are:
What job categories do people searching Weekend Remote Data Scientist jobs in Reston, VA look for? The top searched job categories for Weekend Remote Data Scientist jobs in Reston, VA are:
What cities near Reston, VA are hiring for Weekend Remote Data Scientist jobs? Cities near Reston, VA with the most Weekend Remote Data Scientist job openings:
Data Scientist (Remote Eligible)

Data Scientist (Remote Eligible)

Mathematica

Washington, DC • On-site, Remote

Other

Posted 4 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.  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