Top Remote Data Science Jobs

Develop and maintain sustainability methodologies that translate climate science, GHG accounting standards, and regulatory requirements into auditable product logic. Collaborate with engineers, data scientists, product managers, customers, auditors, and stakeholders; review code, write technical specifications, contribute to implementations and testing, investigate complex sustainability data questions, and document scientific decisions. The role applies sustainability expertise to real-world business data and product capabilities.

This role involves analyzing EHR and insurance claims data to define clinical outcomes, developing AI models, and collaborating with technical experts for manuscript preparation.

Analyze microbiome and longitudinal clinical datasets, develop microbiome metrics and biomarkers using statistics and machine learning, create visualizations and reports, draft clinical research documents, support product and study development, and contribute to scientific publications and proposals.

Lead end-to-end data science for a priority vertical (Insurance), building, validating, and deploying ML models that drive ROAS and lead quality. Partner with stakeholders and ML engineering to monitor live performance, iterate models, and identify new modeling opportunities to improve revenue and media efficiency.

Analyze large-scale structured and unstructured data, develop and validate data models and methodologies, and perform large-scale parallel processing in clustered computing environments (ECL/HPCC, Python, C, SQL) to produce mission-relevant analytic products supporting Intelligence Community objectives.

Founding Data Scientist for Procure-to-Pay working cross-functionally to build models, metrics, simple data pipelines, dashboards, and reports. Analyze complex datasets, produce actionable insights through data storytelling, and partner with leadership to turn business problems into data-driven solutions that impact operations and growth.

As a Staff Data Scientist, you will address complex business challenges using AI and optimization algorithms, collaborate with engineering, define strategies, and implement data product frameworks.

Oversee development, validation, monitoring, and governance of consumer credit risk models used for loss forecasting, credit decisioning, regulatory reporting, and risk management. Apply statistical, econometric, and machine learning methods to PD, LGD, and EAD models; support CECL, stress testing, and macroeconomic scenario analysis. Assess model performance, data quality, and compliance while communicating findings to senior leaders, auditors, regulators, and other stakeholders.

Lead high-complexity data science initiatives improving search ranking, retrieval, relevance, and evaluation. Develop and deploy production machine-learning and NLP solutions, investigate LLM-based ranking features, optimize SQL queries, and work with sparse privacy-preserving data. Define strategies for ambiguous problems, guide other data scientists, collaborate with product teams, and own projects from scoping through production.

The Associate Data Scientist partners with clinical and operational teams to prepare and transform data, develop predictive models, apply statistical and AI techniques, and create actionable insights. Responsibilities include feature engineering, model optimization, data visualization, dashboards, stakeholder presentations, risk management, and Agile collaboration to improve patient care, hospital operations, and organizational outcomes.

Lead data science efforts to inform product and business strategy through quantitative analysis, experimentation, forecasting, and storytelling. Partner with cross-functional teams to define hypotheses, measure impact, influence roadmaps, present insights to senior leadership, and monitor key product metrics to drive value.

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.

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.

Build and deploy predictive models that drive partner action, analyze conversational and unstructured data using NLP techniques, and monitor model performance in production. Own AI data tooling, evaluation frameworks, in-warehouse model configuration, and reusable analytics foundations. The role also establishes modeling standards, evaluates fairness and limitations, collaborates with engineering and product teams, and prioritizes high-impact work across a lean data organization.

Leads enterprise manufacturing AI, machine learning, and Industry 4.0 initiatives across multiple plants. Develops and deploys solutions for predictive maintenance, process and quality optimization, energy efficiency, throughput, and OEE improvement. Establishes scalable data and AI platforms, governance, and MLOps standards while integrating industrial data sources. Leads and mentors data science teams, prioritizes projects, allocates resources, partners with cross-functional manufacturing stakeholders, and presents strategic recommendations and business cases to executives.

Senior Data Scientist partnering with Product, Engineering, and Design teams to analyze user behavior, product performance, and marketplace dynamics. Responsibilities include developing metrics and reporting frameworks, designing experiments, diagnosing business trends, analyzing marketplace behavior, and aligning stakeholders on analytical priorities. The role uses SQL and Python alongside BigQuery, dbt Cloud, Airflow, Tableau, and Statsig, with a focus on product analytics, experimentation, and data-informed decision-making.

Lead ecosystem-level data science and econometric analyses across Xbox, Game Pass, Console, PC, and Store experiences. Evaluate growth, engagement, monetization, experiments, incrementality, and investment ROI using statistical and causal inference methods. Build reusable analytical products and self-service capabilities, influence executive decisions, and mentor team members.

Develop machine learning and AI methods for cybersecurity products using large-scale network telemetry. Analyze anomalies and malicious behavior, engineer features, evaluate models on imbalanced and incomplete data, establish monitoring metrics, and conduct error analysis. Collaborate with threat researchers and software engineers to productionize solutions, research emerging techniques, communicate findings, document methodologies, and mentor data scientists.

Design and deploy deep learning systems for search ranking, personalized recommendations, geospatial search, and pickup-point selection. Translate business goals into ML objectives, lead offline and online evaluation, conduct A/B tests, and partner with engineering on production model serving and latency optimization. Own the production ML lifecycle, including monitoring, drift detection, retraining pipelines, and quality management across international markets.

Develop and operationalize machine learning and statistical models predicting weather-driven transmission and distribution outages. Integrate weather forecasts, infrastructure data, outage records, and geospatial layers into real-time forecasting pipelines. Apply spatio-temporal, probabilistic, and physics-based modeling to support utility decisions during extreme weather and wildfire events. Collaborate with meteorologists, risk modelers, software engineers, and utility customers while using agentic coding tools to accelerate development and validating scientific correctness.

Develop and deploy statistical and machine learning models supporting credit risk, fraud, collections, and marketing. Responsibilities include data exploration, model design, testing, production monitoring, performance analysis, governance, and stakeholder communication. The role partners with Legal and Compliance, translates business questions into analytical solutions, researches new methods, and provides data-driven recommendations to leadership.

Lead end-to-end delivery of strategic data science and AI solutions for AI infrastructure. Work with telemetry and experimentation at fleet scale to build, deploy, and measure predictive and prescriptive models. Partner with stakeholders, present insights, enable adoption, and promote responsible AI. Collaborate closely with data engineers and infrastructure teams to productionize scalable ML solutions.

Leads analytical and technical execution for member onboarding and customer experience portfolios. Develops advanced analytics, predictive models, causal inference, experimentation, AI/ML, and LLM solutions using Python and SQL. Owns solution design, measurement, testing, and performance evaluation while partnering with cross-functional stakeholders. Mentors data scientists, communicates trade-offs, and applies analytical rigor to improve engagement, satisfaction, retention, and healthcare experiences.