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Remote Data Science Jobs

Remote data science jobs are available, but the market is selective: Remoote found 51 active searchable remote roles from 36 companies using the Data Science title filter, with 36 showing salary information, last checked June 16, 2026. Listings change quickly, so use the current results below to confirm fit before applying.

Data Science
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68 jobs found

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Shown 1-10 of 68
Fully remote working arrangement within the United States.Full-TimeData science and AIPosted
Senior Manager, Data Science - AI for BI
Company:Jobgether(11-50 employees, Internet)
  • Lead, coach, mentor, and develop data scientists, analysts, and other technical professionals, including performance management, training, and career development.
  • Direct enterprise data science, AI, machine learning, and advanced analytics initiatives aligned with organizational priorities.
  • Drive AI for BI and conversational analytics capabilities, including natural language querying, AI-assisted reporting, insight discovery, and self-service analytics.
  • Oversee development, deployment, monitoring, and maintenance of machine learning, predictive analytics, generative AI, and optimization models.
  • Establish responsible AI standards, model lifecycle management practices, monitoring processes, and analytics governance frameworks.
  • Collaborate with business and technology stakeholders to identify AI, analytics, and automation opportunities.
  • Lead proofs of concept, pilot programs, and evaluations of emerging technologies and analytical methods.
  • Develop reusable analytics frameworks, standards, and assets, and oversee analytics platforms, tools, processes, data quality, and adoption.
  • Guide advanced statistical analysis and translate complex findings into actionable recommendations for business leaders.
  • Partner with data engineering, business intelligence, and technology teams on data readiness, model performance, and solution deployment.
PythonSQLMachine Learning+3 more

150k - 180k USD per year

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Location: Remote USFull-TimeDigital payments fraudPosted
Principal Fraud Analyst (Data Science), Digital Payments Fraud Strategy
Company:Toast(51-100 employees, Location Based Services, Internet, Information Technology)
  • Lead the definition and evolution of risk frameworks across digital payments, with a focus on guest fraud.
  • Design, develop, and own fraud and risk metrics for decision-making, performance measurement, and strategy.
  • Partner with Product, Engineering, and Risk Operations to translate analytical insights into scalable solutions.
  • Evaluate, integrate, and manage external data sources for risk detection and decisioning.
  • Define data requirements and partner with engineering to build and maintain production-grade data pipelines.
  • Set best practices for measurement and risk modelling in fraud analytics.
PythonSQLData analytics

128k - 205k USD per year

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Remote, GermanyFull-TimeDeveloper toolsPosted
Head of Data Science and Analytics
Company:JetBrains(1001-5000 employees, Developer Tools, iOS, Information Technology)
  • Build and lead a team of data scientists, analysts, and data engineers.
  • Help teams adopt a rigorous experimentation culture and improve how product changes are tested and measured.
  • Analyze the customer journey to improve acquisition, retention, and monetization.
  • Establish scalable analytics foundations, including metric frameworks, data models, and self-service reporting.
  • Partner with engineering teams to design compliant data infrastructure and pipelines.
  • Guide machine learning capabilities for marketing acquisition, product personalization, and operational efficiency.
  • Translate data signals into actionable recommendations for leadership.
  • Define the business unit’s data strategy in support of product and engineering priorities.
Machine LearningData engineeringData science+3 more
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Source API remote eligibility restrictions: United StatesFull-TimeEducation technologyPosted
Program Manager, Data Science Core & GenAI Studio
Company:College Board
  • Establish operating rhythms for planning, status, decision-making, risk reviews, and retrospectives.
  • Align data science, engineering, product, and other stakeholders on dependencies, decisions, scope, responsibilities, milestones, and acceptance criteria.
  • Identify delivery, data, model, compliance, and resourcing risks; drive mitigation and escalate when decisions are needed.
  • Maintain roadmaps, dependency maps, decision logs, risk registers, and executive-ready updates.
  • Translate strategy and business priorities into programs, workstreams, milestones, and measurable outcomes.
  • Lead intake and prioritization, balancing impact, effort, capacity, risk, and sequencing.
  • Establish project readiness criteria, including data access, legal and privacy review, a named business owner, and agreed success measures.
  • Manage handoffs from research and prototyping through production delivery, adoption, and operational ownership.
  • Communicate technical tradeoffs, uncertainty, model limitations, and responsible-use considerations to stakeholders.
  • Partner with Data Science leadership on capacity planning, team effectiveness, and continuous improvement.
AgileMachine LearningRisk Management

120k - 170k USD per year

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Remote, United StatesFull-TimeDevSecOps softwarePosted
Senior Manager, Data Science
Company:GitLab(1001-5000 employees, Developer Tools, DevOps, Open Source)
  • Set a long-range vision and roadmap for Product Data Science and connect team goals to company strategy.
  • Prioritize work and trade-offs across product areas, adapting the team as priorities shift.
  • Partner with Product and Engineering leaders on complex questions, selecting a deep dive, experiment, or production model as appropriate.
  • Raise risks and resource gaps early and present senior leaders with clear options.
  • Hire, coach, and retain the team, build career paths, act on feedback, and make talent decisions.
  • Build a high-trust culture of urgency and accountability, with open communication and predictable progress updates.
  • Set standards for experimentation, causal inference, metric definition, and production modeling.
PythonSQLMachine Learning+4 more

153k - 259k USD per year

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Remote work within the United States or WashingtonDCFull-TimeFederal data analyticsPosted
Dataverse / Data Science Lead (CBP)
Company:Jobgether(11-50 employees, Internet)
  • Lead analytical strategy for complex operational, workflow, technology, and programmatic questions.
  • Serve as the subject-matter expert for Microsoft Dataverse and its analytical applications and integrations.
  • Assess data quality, completeness, sensitivity, lineage, authoritative sources, access requirements, and analytical suitability.
  • Design and maintain reporting-ready data models, transformations, validation rules, business logic, and analytical pipelines.
  • Develop, evaluate, and apply statistical models, machine-learning methods, predictive analytics, and AI or large language model evaluation approaches.
  • Conduct hands-on analysis using Python, SQL, and Dataverse queries, and troubleshoot data and modeling challenges.
  • Collaborate with stakeholders to define baselines, performance measures, outcomes, and interpretations of evidence.
  • Communicate findings, uncertainty, assumptions, data-quality issues, potential bias, and causal limitations to technical and nontechnical audiences.
  • Establish standards for reproducibility, peer review, documentation, validation, quality assurance, and responsible data and AI use.
  • Mentor analysts and coordinate with engineering, platform, application development, and Power Platform teams.
PythonSQLMachine Learning+3 more

111k - 180k USD per year

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Based in BrazilFull-TimeOperations ResearchPosted
Python Data Science | Mid/Senior
Company:Jobgether(11-50 employees, Internet)
  • Design and implement Operations Research solutions focused on mathematical optimization and MILP.
  • Conduct technical and economic feasibility studies and evaluate alternative strategies.
  • Model operational scenarios to support business decisions.
  • Perform reaction stoichiometry analyses and calculate NPV using real-value assumptions.
  • Build and integrate Python optimization models using Pyomo or OR-Tools.
  • Develop and maintain RESTful APIs using FastAPI.
  • Improve code reliability, maintainability, and performance through unit testing, test coverage, and version control.
  • Translate operational requirements with stakeholders into scalable technical solutions.
PostgreSQLPythonSQL+2 more
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This is a fully remote role. Candidates who live near CB offices have the option of being fully remote or hybrid (Tuesday and Wednesday in office).Full-TimeEducational testingPosted
Data Scientist, Data Science Team
Company:College Board
  • Develop machine learning applications using cloud and machine learning technologies.
  • Manage and deliver small- or medium-sized applications and analyses on time and to a high standard.
  • Help identify and build major components of complex machine learning models.
  • Evaluate model effectiveness and fairness, and communicate considerations for applying models in business contexts.
  • Build functions, APIs, and data stores to make predictions and analyses accessible to other systems.
  • Explore existing data, create insights, and drive the collection of new data.
  • Communicate analysis methods and results using accessible language and data visualizations.
  • Create reproducible, documented analyses and models suitable for automation.
  • Improve team productivity and quality through tools, processes, and code structure, and support Agile practices.
  • Advise teams on machine learning projects and governance, and help identify and resolve production issues.
PythonSQLData Analysis+6 more

135k - 163k USD per year

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Listing location: KyivFull-TimeSocial networkingPosted
Head of Data Science
Company:United Tech
  • Build, scale, and develop the Data Science team, including hiring, mentoring, and performance evaluation.
  • Define and execute a Data Science strategy aligned with business priorities.
  • Oversee data science projects from problem formulation through deployment of models into production.
  • Prioritize initiatives based on business impact, including ROI and time-to-market.
  • Collaborate with product managers, analysts, engineers, and C-level executives.
PythonSQLGCP+6 more
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100% telecommuting; can reside anywhere in the US.Full-TimeFinancial analyticsPosted
Director, Data Science
Company:TWG Resources LLC
  • Develop and deploy ML models for applicant generation, ranking, recommendations, and financial analytics.
  • Integrate ML research and innovations into feed, search, discovery, and shopping products.
  • Implement personalization and exploration features to improve product metrics and user engagement.
  • Design and develop frontend and backend solutions with attention to technical design, testing, code quality, and maintainability.
  • Develop and optimize ML models and data pipelines for scalable products and services.
  • Collaborate with engineering, data, business, operations, and program teams to integrate AI/ML solutions and resolve system issues.
  • Support cloud platforms for training and deploying AI/ML solutions, including scalable ML and HPC systems on Google Cloud.
  • Design and maintain reference architectures for diverse AI/ML workloads.
  • Develop and deploy personalized LLMs for search and recommendation systems, and integrate LLMs into products.
  • Execute search and discovery personalization roadmaps and establish stakeholder partnerships.
JavaKafkaSpring Boot+1 more

The expected base pay for this position is $139,818 - $360,000. A discretionary bonus will be provided as part of the compensation package.

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Shown 1-10 of 68
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Is remote data science hiring real right now?

Yes, but it is not a huge open market. Based on Remoote job data from June 16, 2026, the current Data Science search block surfaces 51 active searchable remote jobs across 36 companies. Visible examples include Data Science & Engineering Lead, Senior Manager Data Science & Analytics, Associate Director Media Data Science, Software Engineer - Data Science, and Data Science Intern.

That mix matters because “data science” can mean hands-on modeling, analytics leadership, data engineering, experimentation, media measurement, or software work around ML systems. Read the responsibilities before assuming a listing matches your target role.

How should you screen noisy ML and analytics listings?

Start with the work, not the title. A strong data science listing should say what data you will use, which business decision the models or analysis support, what tools or languages are expected, and whether the role is individual-contributor, management, or hybrid engineering work.

  • For ML-heavy roles, look for modeling, evaluation, deployment, experiment design, or production ML ownership.
  • For analytics-heavy roles, look for metrics, dashboards, stakeholder decision support, SQL, experimentation, or product analytics.
  • For leadership roles, check whether the job is people management, technical strategy, or both.
  • For internships or early-career roles, confirm whether mentorship, scope, and required experience are realistic.

If a posting uses data science keywords but never explains the dataset, business problem, tools, or decision-making context, treat it as a noisy listing and compare it carefully with the roles below.

What can you know about salary before applying?

Salary visibility is relatively strong for this page: 36 of the 51 current Data Science-filtered roles show salary information, based on Remoote listings checked June 16, 2026. This page does not claim a salary range because compensation varies by seniority, location rules, and role type.

If pay is your first filter, compare these listings with remote job salaries before applying. If a role does not show pay, check whether the employer explains compensation later in the process and whether the location or time-zone requirements could affect the offer.

Where should you branch next?

If the current data science set is too narrow, browse the broader remote IT jobs category or compare nearby paths such as remote data analyst jobs. If you are early in your career, start with entry-level remote jobs or remote jobs without experience before spending time on senior data science listings.

Company choice also matters in a small market. Use top remote companies to identify employers with broader remote hiring activity, then return here to check whether their data roles match your skills.

Source: Remoote job listings using the current Data Science title filter, checked June 16, 2026. Counts are a point-in-time snapshot and may change as employers post, update, or close roles.

Remote data science jobs FAQ

Yes. Remoote found 51 active searchable remote jobs from 36 companies using the current Data Science title filter, checked June 16, 2026. Availability changes quickly, so confirm the current results before applying.

Data science titles are used inconsistently by employers. Some roles focus on modeling, some on analytics leadership, and some on software or data engineering around data products. Read the responsibilities, tools, and success metrics before deciding whether a listing fits your target path.

36 of the 51 current Data Science-filtered roles show salary information, based on Remoote job data from June 16, 2026. That is useful for screening, but it does not support one universal salary range because role level, location rules, and responsibilities vary.

Check whether the listing explains the data, business problem, tools, seniority, remote location rules, and interview expectations. Be cautious with vague ML or analytics titles that do not describe the actual work.

Try adjacent searches such as remote data analyst roles, broader remote IT jobs, or entry-level remote jobs if your experience level is lower. Data science supply is real but selective, so branching can help you find roles that match your skills faster.

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