841 Data Scientist jobs available for remote work from home. Apply for positions such as Sr. Data Scientist - Operations & Product (Remote), Principal Product Data Scientist , Senior Data Scientist and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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This role serves as the analytical engine for the company's EHR and RCM products, investigating complex account questions and uncovering root causes. You will collaborate with cross-functional teams to improve platform performance and billing workflows through data-driven insights and experimentation.
Lead and define the data science strategy for product development while serving as a strategic advisor to senior leadership. Drive the integration of emerging AI technologies and mentor team members to foster a culture of technical excellence.
You will apply quantitative analysis and data mining to understand user behavior and inform product strategy. Additionally, you will guide product teams in measuring key metrics and running A/B experiments to improve product performance.
Lead the data strategy and evolve product offerings to simplify money management for customers. Collaborate with product, engineering, and research teams to set standards and drive data-informed decision-making.
Lead and architect the research strategy for applying AI to cybersecurity while driving innovation in LLMs and deep learning. Build production-ready AI systems at scale and mentor scientists to foster a culture of engineering excellence.
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You will collaborate with cross-functional teams to enhance the Lyra platform by developing predictive and generative models. Additionally, you will manage data pipelines and provide actionable insights to support product iterations and clinical logic.
You will design, deploy, and iterate on end-to-end machine learning models to optimize marketplace performance and renter experiences. Additionally, you will collaborate with cross-functional teams to translate complex business problems into measurable technical strategies.
The Data Scientist will develop, maintain, and optimize data pipelines within an Azure Synapse environment to support healthcare data analysis. They are responsible for ensuring data quality, performing exploratory data analysis, and creating derived datasets to meet stakeholder requirements.
You will own the end-to-end machine learning lifecycle, including model development, experimentation, and production deployment to detect fraud. You will also collaborate with cross-functional teams to translate complex fraud patterns into scalable, production-grade ML solutions.
Develop and implement advanced statistical and predictive models to support risk management across credit, financial, and operational domains. Partner with cross-functional stakeholders to analyze model performance, identify risks, and improve organizational decision-making processes.
The Data Scientist II will build and deploy machine learning models and NLP pipelines to support clinical risk intelligence and AI-enabled products. They will collaborate with cross-functional teams to translate research into production-ready, HIPAA-compliant solutions.
Lead the design and operationalization of generative AI and machine learning solutions within clinical and healthcare environments. Act as a senior technical advisor to bridge the gap between clinical stakeholders and engineering teams to deliver secure, measurable AI outcomes.
Lead the design and delivery of advanced AI and machine learning solutions for healthcare and life sciences clients using Azure and Databricks. Act as a senior advisor to stakeholders to ensure solutions are scalable, secure, and aligned with clinical and business objectives.
Lead the design and operationalization of generative AI and machine learning solutions within healthcare and life sciences environments. Act as a senior technical advisor to bridge the gap between clinical stakeholders and engineering teams to deliver secure, measurable AI outcomes.
Lead the design and delivery of advanced AI and machine learning solutions for healthcare and life sciences clients using Azure and Databricks. Act as a senior advisor to stakeholders to operationalize data science models while ensuring compliance, reproducibility, and clinical impact.
Build and maintain auditable data pipelines for clinical and medical imaging datasets while performing statistical analysis for model evaluation. Develop data observability tools and ensure data integrity for regulatory submissions and clinical audits.
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You will partner with the CTO to design and implement production-quality statistical and machine learning systems for residential valuation. Additionally, you will establish technical standards, mentor team members, and translate research ideas into scalable software.
The Senior Data Scientist will develop and evolve AI/ML models to drive personalization initiatives and business value. Responsibilities include end-to-end data science tasks such as data normalization, feature engineering, model deployment, and experimental design.
You will own impactful problem spaces by framing questions, conducting analyses, and implementing solutions with cross-functional partners. Additionally, you will design and evaluate experiments to measure the impact of product changes and uncover root causes of metric movements.
You will design and implement measurement frameworks to evaluate Trust defense effectiveness and lead experimentation programs to drive product and policy decisions. Additionally, you will build statistical and Bayesian models to quantify risk and provide causal interpretations of signals surfaced by machine learning systems.
The Senior Data Scientist will collaborate with product and operations teams to ingest, model, and analyze healthcare data to support care enablement. They will build and maintain scalable data pipelines and models while ensuring internal stakeholders have reliable access to high-quality data.
Lead end-to-end data science projects from problem framing to model deployment while collaborating with cross-functional teams. Develop advanced machine learning models and translate complex quantitative findings into actionable business insights.
The Senior Data Scientist will manage SQL Server data pipelines and modernize ETL processes using Python. Additionally, they will develop Power BI dashboards and perform statistical modeling to support workforce learning and education initiatives.
The Principal Data Scientist will lead the data strategy for the Rentals Shopping pillar, partnering with product leadership to drive growth through rigorous analysis and experimentation. They will also mentor team members and apply advanced modeling techniques to optimize the rental search and conversion experience.
You will lead the Generative AI strategy and roadmap, driving the execution of AI systems while managing a multidisciplinary team of scientists. You will partner with product and engineering teams to embed generative AI into core products and establish rigorous evaluation frameworks for quality and safety.
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The Director will define the multi-quarter vision and technical strategy for Generative AI, leading a multidisciplinary team to integrate AI into core products. They will also establish rigorous evaluation frameworks and drive LLMOps maturity to ensure high-quality, scalable AI deployments.
The incumbent will lead key projects focused on fraud detection, risk analysis, and loss mitigation to optimize business processes. They will collaborate with cross-functional teams to design, execute, and monitor risk control strategies across the customer lifecycle.
Design and build machine learning systems for enterprise search, recommendations, and AI agents while developing evaluation frameworks for LLM-powered applications. Collaborate with cross-functional teams to translate research into production features and define key performance indicators to guide product strategy.
Design and build machine learning systems for enterprise search, recommendations, and AI agents while developing evaluation frameworks for LLM-powered applications. Collaborate with cross-functional teams to translate research into production features and define analytical frameworks to guide product strategy.
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