841 Data Scientist jobs available for remote work from home. Apply for positions such as Consumer Product Data Scientist, #127006 - Data Scientist - Production Machine Learning, Data Scientist / Risk Modeller – Credit Risk and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Analyze complex datasets using the Databricks platform to identify trends and patterns for a high-visibility online product. Develop analytics and dashboards to support client decision-making and validate hypotheses regarding customer retention and churn.
Develop, deploy, and maintain scalable machine learning models and data pipelines in a production cloud environment. Collaborate with engineering and business stakeholders to translate needs into data-driven solutions and monitor model performance.
Develop and maintain credit risk models, specifically focusing on LGD, PD, and CCF models for a banking sector client. This includes data analysis, automating monitoring frameworks, and translating technical results into business insights.
The Principal Data Scientist will set the strategic vision and roadmap for AI/ML solutions within the Telecommunications domain to improve network performance and subscriber experience. They will lead the implementation of cutting-edge models, mentor data science teams, and collaborate cross-functionally to integrate intelligence into scalable products.
The Senior Data Scientist will research and develop machine learning models to solve complex healthcare challenges and improve patient outcomes. They will collaborate with cross-functional teams to integrate these models into production products and mentor junior data scientists.
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Own the end-to-end experimentation and causal inference frameworks to drive data-driven decision-making across the organization. Establish methodological standards and produce rigorous research to support product, marketing, and operations stakeholders.
Develop and deploy scalable data models and experiments to drive evidence-based business decisions for complex organizations. Collaborate in multidisciplinary crews to manage the full lifecycle from data discovery to production-ready AI solutions.
The role involves turning complex lending and risk data into actionable insights and measurement frameworks for credit products. You will lead technical standards for the data science team and partner with product and risk teams to optimize customer access and repayment outcomes.
Lead the development of measurement frameworks and decision systems for credit products like Cash App Borrow and Afterpay. Partner with risk and product teams to analyze customer behavior, evaluate experiments, and drive technical standards for the data science team.
Lead the development of measurement frameworks and decision systems for credit products like Cash App Borrow and Afterpay. Partner with risk and product teams to analyze customer behavior, evaluate experiments, and mentor junior data scientists.
Design and scale advanced detection and diagnostic models for solar and storage assets to identify underperformance and faults. Partner with engineering and operations to deploy these models into the Resolv platform and improve field dispatch recommendations.
Develop and implement machine learning and statistical models to identify and mitigate credit, collections, and fraud risk. Collaborate with stakeholders to transform large datasets into actionable insights that drive business decision-making.
Design and implement AI-powered agents and RAG applications to automate workflows and enhance data retrieval. Collaborate with business teams to build data pipelines and derive actionable insights for global business decisions.
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 processes.
The Senior Clinical Data Scientist will act as the primary data architect for a large-scale commercial real-world evidence registry. They are responsible for designing EHR data extraction pipelines and transforming heterogeneous clinical data into analysis-ready datasets.
Own the data science strategy for RC Capital by building underwriting and fraud detection systems from the ground up. Partner with Product and Engineering to integrate risk signals into customer flows and internal decisioning engines.
Proactively analyze data to identify customer pain points and drive product direction through data-backed hypotheses. Design and deploy production-grade predictive models to power customer-facing features like LTV prediction and benchmarking.
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Lead complex security investigations and analyze large-scale traffic data to improve detection accuracy for security products. Act as a technical bridge between customer-facing teams, security operations, and the core data science research group.
Innovate and improve machine learning models to drive efficient financial decisions for customers. Collaborate with business leaders and technical experts to develop new data sources and implement sound risk management.
The role involves modeling pricing, packaging, and monetization scenarios by analyzing product usage and financial data. You will lead pricing strategies for new product launches and synthesize research into executive recommendations to drive ARR growth.
Design and implement robust statistical models and machine learning algorithms for large-scale predictive analytics. Lead end-to-end data science projects and mentor junior scientists to drive measurable business impact.
Develop advanced ML-based fraud and risk models to reduce financial loss and safeguard user funds. Collaborate across Risk, Compliance, and Product teams to create risk signals and automate decision-making tools.
Lead research to define the AI Shopping roadmap by measuring brand capabilities and optimizing for answer engine outcomes. Design studies, build models, and present data-driven findings to customers to drive business strategy.
Develop and deploy production-ready ML and AI systems to optimize pricing, underwriting, and claims processes. Build end-to-end agentic workflows and measurement frameworks to improve business decision-making across the insurance value chain.
Apply data science to complex product and business problems by evaluating performance and generating actionable insights. Establish analytical processes, monitoring frameworks, and automated ETL workflows to maintain product quality.
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Lead the design and evolution of large-scale fundamental power market models and define analytical approaches for new product capabilities. Collaborate with engineering and product teams to translate customer needs into scalable optimization and forecasting software.
Design and implement advanced data models and machine learning algorithms to solve complex business problems and drive strategic insights. Collaborate with cross-functional teams to translate business needs into analytical solutions and provide thought leadership on data science best practices.
Define and implement the company-wide methodology for experimentation and causal inference to drive data-backed product decisions. Establish statistical standards for small-sample contexts and coach cross-functional teams on rigorous test design.
Develop and implement machine learning and statistical models to identify and mitigate credit, collections, and fraud risk. Collaborate with stakeholders to transform large datasets into actionable insights that drive business decision-making.
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