841 Data Scientist jobs available for remote work from home. Apply for positions such as Senior Data Scientist, Wildnet Technologies - (Data Scientist), Senior Data Scientist (Agentic Solutions) and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Senior Data Scientist produces actionable insights through rigorous analysis and experimentation to optimize lifecycle marketing and monetization strategies. The role involves collaborating with stakeholders to translate business problems into data-driven solutions and automating analytical processes using AI agents.
Develop and optimize Marketing Mix Models (MMM) and Bayesian statistical models to measure marketing effectiveness and support budget allocation. Design attribution frameworks and conduct hypothesis-driven experimentation to generate actionable business insights.
Design, prototype, and deliver AI-powered agentic solutions to solve complex business problems for internal and client-facing use cases. Collaborate with cross-functional teams to translate requirements into scalable designs and evaluate model performance and business impact.
The role involves serving as the primary technical leader for strategic accounts, translating business needs into production-ready data science solutions. You will drive customer outcomes through hands-on execution and guide senior stakeholders in technical decision-making.
Lead the design and implementation of predictive models and causal inference frameworks to measure clinical product effectiveness. Collaborate with engineering and product teams to build scalable ML infrastructure and translate statistical findings into actionable business strategies.
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Develop and optimize Marketing Mix Models (MMM) and Bayesian statistical models to measure marketing impact and support budget allocation. Design causal inference frameworks and automated dashboards to translate analytical findings into business optimization strategies.
Develop and deploy AI solutions ranging from classical machine learning models to advanced Generative AI and multi-agent systems. The role involves end-to-end ownership of data science initiatives, including problem framing, experimentation, and production monitoring.
Develop and implement predictive statistical models to forecast product demand across various geographies to guide inventory and supply plans. Collaborate with demand planners to analyze IBP deviations and provide data-driven insights to improve forecasting accuracy.
Analyze complex microbiome datasets to support research questions and develop novel biomarkers using statistical and machine learning methods. Contribute to scientific publications, research protocols, and the development of new product concepts.
Develop and deploy real-time conversational voice agents and fine-tune clinical AI models for a primary care platform. Build evaluation pipelines and simulation capabilities to ensure model safety and accuracy before production.
Design and validate high-quality datasets for training and evaluating financial-domain LLMs and AI agents. Translate complex financial goals into concrete dataset specifications, rubrics, and statistical evidence to support model risk management.
The role involves designing and validating high-quality datasets and evaluation frameworks for healthcare-specific generative AI models. You will translate clinical goals into measurable specifications and ensure the clinical validity and safety of AI outputs across multimodal health data.
The role involves conducting deep-dive analyses and predictive modeling to drive revenue growth and reduce customer churn for the Enterprise CX team. You will collaborate with cross-functional stakeholders to develop AI/LLM-powered solutions and measure the business impact of Customer Success initiatives.
Develop, deploy, and maintain production-grade machine learning pipelines and models in cloud environments. Collaborate with cross-functional teams to translate business goals into scalable AI and LLM-driven solutions.
Design and execute evaluations for production LLM pipelines to ensure accuracy and quality in clinical data extraction. Build and maintain production-grade data models and a semantic layer to provide reliable business intelligence reporting across the organization.
Design and develop AI and advanced data science solutions integrated with Azure to drive innovation and efficiency. Build machine learning and deep learning models in Python while translating technical results into business implications.
Lead a team in developing analytical infrastructure and predictive algorithms to drive decision-making and profitability for the Pricing Team. Design scalable processes for large-scale data analysis and present business cases to optimize price points.
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Design, build, and scale production-grade generative and agentic AI solutions to drive business impact. Lead model development and deployment across cloud platforms while mentoring a high-performing data science team.
Design and deliver analytical models and decision-support systems to improve business prediction and decision-making. Partner with Engineering teams to translate prototypes into scalable production solutions.
Serve as the primary technical leader for strategic accounts, translating business needs into production-ready data science solutions. Drive customer outcomes through hands-on execution and the guidance of technical decision-making for senior stakeholders.
Lead the design and deployment of advanced predictive models, NLP solutions, and AI-powered tools to identify and act on caregiver risk. Collaborate with data engineering to build MLOps pipelines and mentor junior data scientists to improve population health outcomes.
Own the modeling and experimentation for global pricing, focusing on price elasticity and willingness-to-pay models. Build and monitor AI-driven pricing intelligence tools and analytical infrastructure to optimize margin and merchant retention.
Build and own end-to-end models for vendor matching, order routing, and supply chain optimization. Mentor senior data scientists and architect autonomous agentic AI systems to improve operational efficiency.
Own and ship end-to-end machine learning models for vendor matching, order routing, and supply chain optimization. Implement decision logic for agentic AI and quantify the business impact of data science initiatives.
Drive the technical roadmap by translating complex business requirements into scalable machine learning implementations. Take end-to-end ownership of the model lifecycle, from initial scoping to production deployment and maintenance.
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Develop, validate, and maintain SDTM and ADaM datasets using R and SAS following CDISC standards. Collaborate with biostatistics and clinical data teams to support clinical trial deliverables and ensure regulatory compliance.
Transform complex operational data into actionable insights to improve productivity, quality, and supply-chain performance. Develop predictive models and data pipelines to support data-driven decision-making across manufacturing and engineering teams.
Design and implement machine learning and computer vision algorithms for identity document analysis and fraud detection. Collaborate with cross-functional teams to deploy these solutions across cloud, server, and mobile environments.
Develop and deploy predictive models and machine learning algorithms to solve complex business challenges. Collaborate with cross-functional teams to transform large datasets into actionable insights and data-driven strategies.
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