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Remote Scientist Jobs in Silver Spring, MD (NOW HIRING)

Scientific workflows * Automated processing techniques * Utilize advanced processing tools ... Remote sensing phenomenology * Image formation processes * Exploitation products and methodologies

Data Scientist

Chantilly, VA · On-site +1

$200K - $240K/yr

None Potential for Remote Work: ORA_ON_SITE Description  SAIC is hiring a Data Scientist to deliver Systems Engineering Technical Advisor (SETA) support a program based in Chantilly, VA. This role ...

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

This is a full-time, salaried, remote position. Candidate must reside within the Continental U.S ... Mentor junior data scientists and establish best practices. Required Qualifications * Bachelor ...

Senior Data Scientist

Herndon, VA · On-site +1

$160K - $190K/yr

This is a full-time, salaried, remote position. Candidate must reside within the Continental U.S ... Mentor junior data scientists and establish best practices. Required Qualifications * Bachelor ...

Remote Work: No Job Number: R0241573 Location: Alexandria,VA,US Share job via: Share Data Scientist The Opportunity: In this role, you will apply data science techniques and methods and leverage a ...

The percentage of remote work will vary based on client requirements/deliverables Fun stuff you will do: * Work closely with a tight-knit team of data scientists, software developers, network ...

Showing results 21-40

Remote Scientist information

See Silver Spring, MD salary details

$86.3K

$131.3K

$176.8K

How much do remote scientist jobs pay per year?

As of Aug 11, 2026, the average yearly pay for remote scientist in Silver Spring, MD is $131,322.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,700.00 and $148,300.00 per year, depending on experience, location, and employer.

Is 40 too late to become a remote scientist?

Age is not a barrier to becoming a remote scientist, as the field values skills, experience, and education. Many scientists transition into remote roles later in their careers, often leveraging advanced degrees, research experience, and familiarity with scientific tools and software. Continuous learning and staying current with industry developments can support a successful transition at any age.

What is a remote scientist?

A Remote Scientist is a professional who conducts scientific research, analysis, and experiments while working remotely, often using digital tools and virtual collaboration platforms. They may work in various fields, including environmental science, data science, biotechnology, and engineering. Remote Scientists communicate their findings through reports, presentations, or virtual meetings with colleagues and stakeholders. This role requires strong problem-solving skills, self-discipline, and proficiency in using remote research tools.

What remote scientist jobs are there?

Remote scientist jobs include roles such as research scientists, data scientists, laboratory scientists, and environmental scientists. These positions often require specialized knowledge, relevant degrees, and skills in data analysis, laboratory techniques, or scientific research, and may involve collaboration through digital tools and virtual meetings.

What does a remote scientist do?

A typical day for a Remote Scientist often involves analyzing datasets, designing experiments or simulations, collaborating with team members via video calls or shared digital platforms, and preparing reports or presentations. Depending on their specialization, they may spend time running remote experiments, writing scientific papers, or contributing to grant proposals. While much of the work is independent, regular virtual meetings are held to ensure alignment with projects and to discuss research progress. This structure allows Remote Scientists to balance focused research time with teamwork and ongoing professional development.

What skills and qualifications are needed to thrive as a remote scientist?

To thrive as a Remote Scientist, you need a strong grounding in scientific research methods, data analysis, and a relevant advanced degree such as a Master's or Ph.D. Tools like statistical software (e.g., R, Python), laboratory management systems, and secure data-sharing platforms are frequently used, along with certifications in specialized areas if required. Exceptional written and verbal communication, self-motivation, and organizational skills are essential for effectively collaborating within remote teams and managing independent projects. These abilities ensure remote scientists maintain high research standards, deliver impactful findings, and successfully bridge the gap between virtual collaboration and tangible scientific progress.

What are the most commonly searched types of Scientist jobs in Silver Spring, MD? The most popular types of Scientist jobs in Silver Spring, MD are:
What are popular job titles related to Remote Scientist jobs in Silver Spring, MD? For Remote Scientist jobs in Silver Spring, MD, the most frequently searched job titles are:
What cities near Silver Spring, MD are hiring for Remote Scientist jobs? Cities near Silver Spring, MD with the most Remote Scientist job openings:
Infographic showing various Remote Scientist job openings in Silver Spring, MD as of August 2026, with employment types broken down into 1% Internship, 1% As Needed, 82% Full Time, 12% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $131,322 per year, or $63.1 per hour.

Data Scientist (Remote Eligible)

Mathematica

Washington, DC • On-site, Remote

Full-time

Re-posted 2 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