841 Data Scientist jobs available for remote work from home. Apply for positions such as Data Scientist en chef, Croissance, Senior Data Scientist, Growth, Staff Data Scientist, Growth and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will collaborate with cross-functional teams to identify growth opportunities and improve user acquisition, activation, and retention. You will also define key performance indicators and build data-driven models to inform business decisions and product strategy.
You will partner with product, engineering, and marketing teams to identify growth opportunities and drive business decisions through experimentation and data analysis. Additionally, you will build dashboards, models, and self-serve tools to improve visibility into user behavior and business performance.
You will partner with product, engineering, and marketing teams to identify growth opportunities and drive business decisions through experimentation and data analysis. You will also define KPIs, build dashboards, and develop models to improve visibility into user behavior and financial performance.
The Senior Data Scientist will lead the development of advanced analytical solutions, including NLP and LLM/RAG frameworks, to address complex healthcare policy challenges. They will collaborate with stakeholders to design data-driven products that improve program oversight and health outcomes for Medicaid and CHIP programs.
The Senior Data Scientist will design and implement rigorous evaluation systems for football machine learning models to ensure accuracy and reliability. They will build experimentation tooling and collaborate with subject-matter experts to validate model performance before production deployment.
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Lead the design and implementation of advanced machine learning models and predictive analytics to solve complex business problems. Collaborate with cross-functional teams to define project requirements while mentoring junior data scientists and promoting data-driven decision-making.
Develop and maintain fraud detection models throughout the full development lifecycle, from data acquisition to production monitoring. Collaborate with cross-functional teams to research new fraud types and build foundational modeling for financial risk products.
You will lead product strategy through measurement, experimentation, and causal analysis while partnering with cross-functional teams to drive growth. Additionally, you will build self-serve data tools, define team-level KPIs, and mentor junior data scientists to improve data literacy.
Partner with product, design, and engineering teams to drive data-motivated decision-making and uncover user behavior insights. Design, execute, and evaluate product experiments while building scalable dashboards to democratize data across the organization.
You will be responsible for developing, deploying, and maintaining production-grade machine learning models within a cloud environment. The role involves collaborating with cross-functional teams to build scalable data pipelines and enhance product offerings using AI and LLM capabilities.
You will lead high-impact engineering projects by collaborating with customers to develop AI and cloud-based solutions. Additionally, you will oversee data acquisition, coach engineers on best practices, and drive strategy for model development and data ethics.
You will lead the end-to-end delivery of data science solutions by acquiring and preparing datasets, developing scalable models, and driving evidence-based business decisions. Additionally, you will collaborate with multidisciplinary teams to solve complex customer challenges while mentoring engineers and promoting data science best practices.
You will lead the end-to-end lifecycle of data science projects, from data acquisition and model development to deployment in production environments. Additionally, you will collaborate with cross-disciplinary teams and customers to drive evidence-based business outcomes and mentor team members in best practices.
The Data Scientist will design and develop advanced machine learning models and algorithms to extract insights from large HR datasets. They are responsible for the end-to-end MLOps lifecycle, including research, deployment, and communicating complex findings to non-technical stakeholders.
You will lead complex machine learning projects and define technical standards for the Data Science and AI department. Your role involves mentoring senior staff, establishing long-term technical vision, and bridging academic research with production systems.
The Principal Data Scientist will design and implement scalable AI solutions to automate business decision-making processes. They will also mentor junior team members and collaborate with cross-functional teams to deliver production-ready AI models.
The Principal Data Scientist will lead the development of digital pathology AI models to predict clinical outcomes and pathological features. They will also coordinate cross-functional team efforts, manage project execution, and collaborate with internal and external experts to build evidence for model utility.
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The Data Scientist will build predictive models for home lending purchasers and refinancers while analyzing user behavior to optimize web-based lending tools. They are expected to interpret statistical results for stakeholders and champion data science initiatives within the home lending area.
You will build and deploy machine learning models to prevent fraud while collaborating with clients to translate complex data insights into actionable risk strategies. Additionally, you will develop performance metrics and automate dashboards to monitor risk products and optimize decision-making across the business.
You will own the foundational marketing machine learning models, including customer intent modeling and next-best-action frameworks. Additionally, you will lead marketing mix modeling and attribution efforts to drive strategic investment decisions across the organization.
You will build and maintain trusted product data assets while defining measurement frameworks for product health and customer lifecycle. Additionally, you will partner with cross-functional teams to influence product strategy and drive company decisions through clear analytical recommendations.
The Data Scientist will analyze and interpret telemetry data from various sources to define business KPIs. They will also be responsible for manipulating datasets and applying machine learning techniques to support business objectives.
Design, develop, and optimize Generative AI and machine learning solutions, including RAG pipelines and AI agents. Collaborate with engineering teams to deploy, monitor, and evaluate models for enterprise-scale applications.
The Data Scientist will develop and validate econometric and machine learning models to provide actionable insights for energy utility clients. They will also communicate complex technical findings to non-technical audiences to inform critical business decisions.
Design, develop, and deploy machine learning models to address complex business challenges while collaborating with cross-functional teams. Lead experimentation, mentor junior data scientists, and extract actionable insights from large datasets to drive organizational decision-making.
The Senior Data Scientist will develop statistical models and machine learning algorithms to optimize patient enrollment and clinical trial management. They will also build scalable data pipelines and ensure all analytical practices comply with healthcare privacy regulations like HIPAA and GDPR.
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Lead the design and delivery of statistical and machine learning solutions to drive high-impact business decisions. Own complex data problems end-to-end, from initial framing to production deployment and monitoring.
You will establish the data science function from the ground up, defining the methods, standards, and infrastructure for a new venture. You will own the evidence layer, turning product and customer signals into defensible knowledge to drive client outcomes.
Lead the design, development, and deployment of machine learning solutions to drive business impact and optimize customer experiences. Partner with cross-functional teams to identify opportunities, analyze experiments, and build scalable AI-powered products.
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