Top Remote Data Science Jobs

The Data Scientist will analyze data for risk and trading in Daily Fantasy Sports, develop predictive models, and monitor real-time data.

Assists with analyzing complex datasets, developing predictive models for insurance underwriting, pricing, claims, and retention, and building data pipelines and automated reporting. Collaborates with actuarial, underwriting, claims, product, and data engineering teams to solve business problems. Communicates insights through visualization and data storytelling, monitors model performance and data quality, and explores new data sources and modeling techniques while supporting insurance model governance.

Develops pricing and promotion optimization models using forecasting, deep learning, predictive modeling, and advanced analytics. Leads analytics solution development, interprets large datasets, communicates recommendations to technical and business audiences, and collaborates with cross-functional partners. The role also builds reusable algorithms, documents analytical solutions, and explores new data science techniques to improve profitability, efficiency, and customer experience.

Analyze, clean, and validate complex healthcare data; develop statistical, machine learning, and AI models; implement agentic workflows, RAG solutions, and model fine-tuning; deploy and monitor models in production; collaborate with technical and business teams; conduct research; and document and communicate findings.

Design and build thermal performance analytics, Python-based engineering models, scalable data flows, and Edge-native applications for power plant asset performance management. Integrate historian, cloud, Edge, and industrial systems; develop automation, diagnostics, KPI validation, and root-cause workflows; support customer deployments; and lead architecture discussions while mentoring engineering teams.

Supports data processing, statistical and machine learning model updates, marketing analyses, reporting, and data automation. Uses R or Python, SQL, BigQuery, BI tools, and spreadsheets to prepare datasets, maintain media-mix models, analyze results, and communicate insights to technical and non-technical audiences. Collaborates with Engineering, Reporting, Product, Paid Media, and Data Science teams while developing advanced analytical skills.

Leads the end-to-end design, deployment, and governance of AI-driven pricing models across merchandise categories. Builds data acquisition and curation pipelines, applies machine learning and Gen AI to product matching and data cleanup, integrates competitive pricing data, and develops experimentation infrastructure. Partners with product, engineering, analysts, and executives to optimize pricing performance, investigate anomalies, guide AI adoption, and establish modeling standards while mentoring data science and pricing teams.

Lead research and experimentation to measure ad campaign performance and effectiveness. Design evaluation frameworks, build measurement solutions, develop models for lift, conversion, and attribution, run experiments and analyses, partner with product/engineering/design/sales, present insights, mentor teammates, and foster technical community and culture.

Lead design, execution, and interpretation of A/B tests and quasi-experiments; apply causal inference methods; partner with product, engineering, and marketing; mentor data scientists; build experimentation frameworks; extract and analyze data using SQL and Python; communicate results to stakeholders.

As a Data Scientist, you'll build production-grade ML systems for HVAC efficiency, working on scaling models, database optimization, and real-time monitoring systems.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.

Conduct data science research on experimental methodologies and causal modeling, develop tools to analyze experimental data, prototype improvements to platform features, and communicate results to internal teams and external stakeholders to drive product and research decisions.

Conduct data science research advancing experimental and causal methodologies; develop robust tools and prototypes to analyze experimental data; improve core platform features; and communicate findings to internal teams and external stakeholders to drive insights and product improvements.

Design and deploy predictive forecasting and analytics to support Revenue operations. Build models for forecasting, churn, expansion, and pipeline analytics; create scalable dashboards; partner with Revenue Operations, Finance, and Data Engineering to improve data quality, KPI governance, and executive reporting to drive data-driven decisions and AI readiness.

Own end-to-end modeling for vendor matching, order routing, and supply-chain optimization. Build predictive, causal, RL and OR solutions; design autonomous decision logic; quantify counterfactual impact; ship production models with data engineering; mentor senior data scientists; write technical design docs; partner on quarterly priorities and expand into revenue cycle and finance domains.

Join a talent network connecting senior/staff data scientists with VC-backed startups. Work with product and engineering to design experiments, build predictive and causal models, productionize analytics, create dashboards, mentor teammates, and shape data strategy to drive product and business outcomes.

Join a SignalFire talent network to be matched with VC-backed startups seeking Senior/Staff Data Scientists. Responsibilities include experimental design and analysis, predictive and causal modeling, productionizing models, building metrics and dashboards, advising product and business teams, mentoring other data scientists, and shaping data strategy and tooling at fast-moving startups.

Design, build, and deploy predictive models for risk and fraud using R, Python, SAS, and SQL. Analyze large datasets, develop cloud-based analytic solutions, validate scoring code with stakeholders, and document statistical methodologies and best practices.

Support ARNG CFO analytics by preparing and facilitating PPBC-G forums, coordinating across staffs, designing and executing data analyses and ML models, and developing/enhancing websites, applications, and secure database access for program portfolio analytics and executive presentations.

As the first Data Scientist, you will build models and algorithms from scratch, impacting the company's success in optimizing insurance portfolios.

Assist senior data scientists with data collection, preprocessing, cleaning, and basic statistical analysis. Support model development, perform basic visualizations, and document processes and findings while learning and applying data science techniques.

Senior individual contributor who drives product analytics, experimentation, and applied modeling. Owns growth and performance analyses, designs experiments with robust statistical evaluation, builds repeatable reporting, and partners with Product, Engineering, Operations, Clinical, and Finance to translate data into actionable product and operational decisions.

Perform data cleansing, ETL, and preprocessing; analyze Retail CPG sales, inventory, and customer data; build predictive models for forecasting and segmentation; research and deploy Agentic frameworks and intelligent agents; produce visualizations and communicate insights to cross-functional stakeholders to optimize supply chain, marketing, and customer experience.

Lead experimentation and causal inference at company-wide scale: define methodology, own statistical approaches for small samples and clustered data, apply causal methods when experiments arent feasible, run experiment review, build tooling and curriculum, and partner with analytics and AI/ML teams to ensure decision-grade results.

Design and run exploratory analyses, build Python-based data pipelines, apply statistical modeling, graph algorithms and ML to multi-INT datasets, and develop interactive dashboards (Power BI/Tableau/Grafana). Mentor junior staff, brief senior leadership, and produce technical reports and documentation in a DoD/IC environment.