Top Remote Data Science Jobs

Lead end-to-end data science projects including predictive modeling, algorithm design, and data pipelines. Build campaign-focused models (turnout, partisanship), perform exploration and visualization, translate insights into memos/presentations, collaborate with engineering to productionize models, mentor junior data scientists, and prototype emerging AI solutions for product impact.

Lead data science work embedded in the newsroom: identify high-impact problems, build and productionize predictive and explanatory models, own core metrics/measurement, apply causal inference and experimentation, translate findings for senior stakeholders, and mentor junior data team members to improve analytic standards and adoption.

Lead end-to-end data science initiatives for commercial property or homeowners insurance: acquire and prepare data, build and validate predictive models, deploy and monitor production models, ensure governance and documentation, advise teams, and evaluate emerging ML/AI techniques to improve pricing, risk selection, and underwriting outcomes.

Lead methodology and modeling for causal inference, experimentation, and predictive analytics. Design and evaluate experiments, build production-ready models and evaluation pipelines, collaborate with Product/Economics/Research/Engineering, communicate findings to varied audiences, and document institutionalized analytical practices.

Embed in a core business area to define problems, build metrics/reports, run analyses and experiments, and drive data-informed product, growth, AI, or partnership outcomes end-to-end.

Embed within a business unit to define problems, build analyses, metrics, experiments, and reports, and drive data-informed recommendations and execution across growth, product, AI/automation, or partnerships.

Lead measurement and optimization for performance marketing: design experiments, build and deploy statistical and ML models (LTV, propensity, forecasting), evolve incrementality testing, develop ETL pipelines and dashboards, translate findings into actionable recommendations, and collaborate cross-functionally to drive user growth and marketing strategy.

Embedded within a core business area, own end-to-end analytics: define problems, build metrics/reports, run analyses and experiments, surface insights, recommend actions, and drive outcomes with stakeholders.

Embed within a business unit (growth, product, AI/automation, or partnerships) to define problems, build metrics/reports, run analyses and experiments, and drive data-informed recommendations end-to-end. Execute analyses in SQL/Python, communicate findings to stakeholders, and ensure outcomes are implemented to improve key business metrics.

Lead product data scientist shaping growth strategy, experimentation, and metrics. Build self-service analytics, size opportunities, design and analyze experiments with product and engineering, drive activation/engagement/monetization insights, and evolve the company's experimentation culture.

The Senior Data Scientist will partner with multiple departments to deliver impactful data solutions, champion data adoption, and evolve data science standards.

The Lead Data Scientist will develop advanced analytical solutions for pricing and customer insights in pet insurance, mentor teams, and collaborate with stakeholders.

Deliver end-to-end data science projects using machine learning and deep learning, collaborate with stakeholders, and support client engagement through analytical planning and solution design.

The Senior Data Scientist will lead data science strategy, develop models for lead qualification, fraud detection, and underwriting, and collaborate with product and engineering to enhance financial products.

Design, deliver, and maintain revenue-optimizing analytics and optimization products. Identify commercial opportunities, build models (forecasting, RL, optimization), process large/unstructured data, coordinate stakeholders and IT, implement end-to-end solutions, and support Analytics team development.

Lead development of time-series and econometric models (ARIMA, VAR, state-space, WLS, panel data) and Bayesian probabilistic frameworks. Use causal inference and stochastic processes to produce actionable insights, work with large datasets on Databricks, communicate results to stakeholders, and mentor junior team members.

Design and deploy scalable statistical and machine learning models on large health datasets (claims, EHR, pharmacy). Prototype NLP search, resolve identity/merge anomalies, collaborate with product, engineering and analytics to productionalize models, monitor performance, and drive data-driven product improvements.

Lead end-to-end data science experiments on messy federal and private data: run EDAs, graph analytics and GNNs, perform probabilistic entity resolution, apply LLM-based NER, train interpretable classifiers and anomaly detectors, document reproducible pipelines, and present rigorous, statistically sound findings to operational stakeholders.

Lead data science across Growth and Membership Operations: define problems, build scalable data models and pipelines, develop analytical and ML solutions, partner cross-functionally, and integrate AI tools to optimize sales, marketing, telesales, and enrollment operations.

The Senior Associate Scientist will analyze and visualize data, collaborate on screening strategies, and validate hits for drug discovery using the EMMI platform.

Lead a data science team to design, build, and deploy large-scale, real-time AI/ML solutions (forecasting, diagnostics, LLM chatbot, retention models, optimization) to optimize GPU cloud gaming performance and user experience.

The Senior Data Scientist will design and deploy machine learning models, analyze complex datasets, develop analytical solutions, and mentor junior team members in a remote environment.

The Senior Data Scientist leads data-driven initiatives, optimizing analytics for business decisions, mentoring staff, and ensuring data quality across healthcare projects.

The Principal Data Scientist will design, develop, and deploy machine learning models, innovating methodologies and collaborating across teams to enhance financial decision-making and risk management.

As a Lead Data Scientist, you will shape data strategy, develop predictive models, analyze healthcare datasets, and collaborate with teams to enhance MDCalc's clinical decision tools.