841 Data Scientist jobs available for remote work from home. Apply for positions such as Clinical Data Scientist (Remote), Sr Data Scientist, Graph Data Scientist and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Lead end-to-end medical research projects and extract clinical insights from EMR data using LLM-based feature engineering. Develop data pipelines and build patient cohorts to enrich the company's proprietary healthcare data catalog.
Develop statistical models and machine learning pipelines to detect threats and behavioral anomalies in assessment datasets. Create executive dashboards and reports to communicate security risks and insights to senior leadership.
Develop advanced graph analytics and machine learning models to identify fraud rings and hidden relationships within federal programs. Design and optimize graph data pipelines, models, and schemas to support large-scale, high-complexity networks.
Lead the design and deployment of advanced analytics and AI-enabled fraud detection capabilities for federal oversight activities. Provide technical leadership and mentorship to teams while collaborating with government stakeholders to prevent waste and abuse.
Lead the data science strategy and oversee the design and implementation of scalable scoring models to drive business impact. Mentor junior data scientists and collaborate with cross-functional teams to integrate data science outputs into production systems.
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Lead the development of real-time, cross-vertical personalization and ranking systems using transformer architectures and graph-based retrieval. Drive the AI transformation of the app by implementing RAG systems and optimizing customer engagement through data-driven decision-making.
Responsible for analyzing project and trial data, statistical programming, and developing reusable programs and visualizations. Provides support for clinical development phases, including study planning, sample size determination, and reporting.
Apply advanced analytics, machine learning, and AI techniques to solve complex business challenges across the enterprise. Develop and deploy sophisticated data science solutions to drive operational efficiencies and enhance decision-making.
Architect, develop, and deploy machine learning systems to production, specifically focusing on chatbots and search. Apply the scientific method to build LLM-powered applications and participate in Data Science chapter decisions.
Develop and implement new models and algorithms to enhance retail forecasting, pricing, and promotion strategies. Process and verify data integrity while collaborating with cross-functional teams to translate complex data into business solutions.
Develop and test data extraction software for structured and unstructured EHR content while tuning and training LLMs. Coordinate data set curation and quality assurance to deliver complex health data products.
Develop and test data extraction software for structured and unstructured EHR content while leading the curation of datasets for AI model training. Tune and train Large Language Models (LLMs) to improve health data processing and analysis capabilities.
Design and deploy machine learning models to optimize payment performance, anomaly detection, and intelligent routing. Own the full data science lifecycle from research and feature engineering to production deployment and monitoring.
Design, develop, and scale AI/ML solutions with a focus on Generative AI, including RAG-based systems and conversational bots. Collaborate with cross-functional teams to translate business needs into production-ready AI tools that enhance customer experience and operational efficiency.
Define the technical strategy and architect enterprise-wide AI capabilities to support healthcare business goals. Lead the research and deployment of advanced ML solutions, including LLM agents and predictive engines, while establishing organizational standards for AI governance.
Lead the design and deployment of production-grade ML and Generative AI solutions to enhance the digital workplace experience. Collaborate cross-functionally to implement intelligent assistants, predictive analytics, and workflow automation at scale.
Lead the end-to-end AI product lifecycle from identifying user pain points to training foundation models and measuring real-world impact. Collaborate with cross-functional teams to translate business goals into a technical AI roadmap and maintain production-grade training pipelines.
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Collaborate with a multidisciplinary team to design and implement innovative data solutions that generate business value from big data and AI. Manage the entire project value chain from data collection and processing to the production of machine learning models.
Own the evaluation loop for all AI products, including pre-launch quality gates and post-launch monitoring. Build quality dashboards and translate failure patterns from production traffic into actionable product fixes.
Develop and improve frameworks for estimating the long-term causal impact of product changes on the platform. Build tooling to evaluate heterogeneous impacts and apply advanced econometric and experimental methods to business problems.
Lead the technical strategy and development of advanced generative AI and multimodal vision systems. Drive the transition of research models into production-ready capabilities while mentoring other scientists.
Optimize and evaluate AI products for medical professionals using extensive datasets and create product and client-facing analytics. Collaborate with product leaders to define data strategy and lead projects from ingestion to final recommendations.
Develop and deploy machine learning and NLP models for topical classification, entity extraction, and user intent detection. Collaborate with cross-functional stakeholders to translate business requirements into scalable data science pipelines and mentor junior team members.
Develop and deploy scalable NLP and machine learning models for tasks such as entity extraction, sentiment analysis, and topical classification. Collaborate with cross-functional stakeholders to translate business requirements into technical solutions and mentor junior team members.
Lead the evolution of recommendation systems into generative and agentic experiences using LLMs and real-time intent layers. Partner with leadership to drive the AI research agenda and implement ML-driven bot detection and customer segmentation.
Lead the development of evaluation frameworks and metrics to validate the performance and safety of autonomous robotaxis. Collaborate with engineering teams to identify edge cases and ensure the autonomy stack meets rigorous safety standards for commercial launch.
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Lead the development of data science within the product team to create statistical models that enhance customer experience and product features. Partner with cross-functional teams to identify high-impact opportunities and mentor product analysts in experimentation and modeling best practices.
Design and maintain measurement frameworks and statistical models to quantify viewership and brand exposure across broadcast and streaming platforms. Collaborate with product and engineering teams to translate raw data into client-ready sponsorship valuations and KPIs.
Develop intelligent solutions combining advanced analytics and Generative AI to solve real business challenges using Python and Azure. Design, test, and deploy AI models while creating technical documentation and supporting sales prospecting efforts.
Lead the design and deployment of advanced analytics and machine learning solutions to detect fraud, waste, and abuse within a federal environment. Provide technical leadership and mentorship to data scientists while collaborating with government stakeholders to translate operational requirements into technical solutions.
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