809 Data Scientist jobs available for remote work from home. Apply for positions such as DLCP Technology Data Scientist, Staff Data Scientist - Payments, Data Scientist Semi Senior - Databricks – Causal Inference & Growth Marketing #5 and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Technology Data Scientist will develop and maintain predictive models and machine-learning solutions to transform complex data into actionable insights. They will collaborate with engineering and business teams to design data pipelines, automate processes, and ensure data quality across the organization.
You will partner with product and business leaders to transform data into strategic insights that drive decision-making and product innovation. Additionally, you will lead complex analytical initiatives and build scalable data solutions to support the company's payments ecosystem.
Design and analyze experiments to measure marketing impact and optimize growth strategies using causal inference techniques. Collaborate with cross-functional teams to build predictive models and data pipelines on the Databricks platform.
The Principal Data Scientist will lead the data science function, owning the end-to-end machine learning strategy and MLOps infrastructure. They will collaborate with cross-functional teams to build predictive models and analytical data models that support clinical interventions and operational performance.
You will lead data science and machine learning initiatives from problem definition through production deployment and impact measurement. This role involves mentoring team members, setting technical direction, and collaborating with cross-functional partners to improve student and business outcomes.
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You will lead end-to-end data science projects, scoping business problems and developing reliable AI models and agents. Additionally, you will mentor team members and communicate complex technical solutions to both technical and non-technical stakeholders.
You will own well-defined components of AI projects, from data modeling and evaluation to infrastructure development. You will collaborate with engineers and domain experts to deploy reliable models and agents into production.
You will explore multimodal datasets to build features and pipelines while developing and testing models and agents under the guidance of senior staff. The role involves writing clean, production-ready code and continuously learning new methods as the field evolves.
The Data Scientist will develop statistical and machine learning models to detect kinematic behaviors using live and historical data. They will also collaborate with software engineers and stakeholders to build and sustain data pipelines and analytic applications.
Lead the design and implementation of statistical and machine learning models to support mission-focused software capabilities. Collaborate with cross-functional teams to process, analyze, and visualize complex data for actionable insights.
You will frame business problems as modeling problems and build predictive models to create measurable value for the enterprise. You will also collaborate with product and engineering teams to deploy these models into production and set the science agenda for your product area.
You will frame business problems as modeling challenges and build predictive models to drive measurable value for enterprise products. You will also collaborate with engineering teams to deploy these models into production while maintaining rigorous standards for quality and reproducibility.
The Principal II Data Scientist will produce innovative healthcare solutions and thought leadership through advanced AI/ML modeling and exploratory data analysis. They will collaborate with subject matter experts and engineers to translate prototypes into scalable products and services.
The Senior Data Scientist will develop and implement complex machine learning algorithms and statistical models to solve intricate data problems. They will also serve as a subject matter expert to provide strategic guidance on data exploration, product design, and cross-functional collaboration.
The Machine Learning Engineer will design and deploy LLM-powered knowledge systems and predictive models to optimize climate policy and renewable energy deployment. They will manage the full modeling lifecycle, including data infrastructure, causal analysis, and MLOps pipelines to support data-driven climate solutions.
The Geospatial Data Scientist will design, implement, and manage geospatial data capabilities to support spatial analysis, digital mapping, and AI-enabled initiatives. They will also collaborate with data engineering teams to ensure geospatial datasets are correctly integrated into ingestion, transformation, and publication workflows.
The Data Scientist will design, develop, and maintain advanced machine learning and AI models to identify patterns and support high-impact decision-making. They will collaborate with stakeholders and technical teams to translate complex business questions into actionable analytical findings.
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The candidate will develop and maintain advanced analytical solutions, including data pipelines and dashboards, to support FDA post-market surveillance initiatives. They will collaborate with stakeholders to perform safety signal detection and translate complex data into actionable regulatory insights.
The Associate Data Scientist will develop and implement statistical and machine learning models while managing large datasets to support business decision-making. They will also contribute to data science products, pipelines, and reporting while utilizing AI-assisted tools to accelerate research and code development.
The role involves leading the migration of an R-Framework to the cloud and optimizing integration with REST APIs and JSON structures. Additionally, the developer will drive large-scale data reconciliation and support the Risk department in streamlining deployment pipelines.
The Principal Clinical Data Scientist manages the operational clinical science function, overseeing data cleaning, review, and visualization from study startup through database lock. They serve as a subject matter expert, providing scientific input to project teams and ensuring compliance with clinical guidelines and study protocols.
The Junior Data Scientist will collaborate with a multidisciplinary team to develop, integrate, and optimize machine learning and generative AI models. They will also be responsible for analyzing client data, preparing datasets, and documenting technical approaches to ensure reproducibility.
The Senior Data Scientist will design, develop, and deploy enterprise-grade machine learning solutions to support strategic business initiatives. This role involves managing the complete data science lifecycle, from translating business problems into analytical models to monitoring performance in production environments.
You will own the geospatial data science function, defining technical strategy for data ingestion and pipeline architecture. You will also lead the development of environmental hazard models and translate complex scientific findings into actionable business intelligence products.
You will act as a strategic partner to product, marketing, and finance leaders to optimize decision-making through rigorous experimentation and causal inference. Additionally, you will design and own technical tools for forecasting, spend optimization, and marketing attribution to drive business impact.
You will deliver analytics and insights to support clinical operations by designing and implementing data solutions on Google Cloud Platform. This role involves automating manual data processes and developing business logic metrics for Tableau dashboards to support prior authorization insights.
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The Principal Clinical Data Scientist manages the operational clinical science function, overseeing data cleaning, review, and visualization from study startup through database lock. They serve as a functional lead, providing scientific insights, managing cross-functional teams, and ensuring adherence to study protocols and regulatory standards.
The Data Scientist designs and delivers statistical, machine learning, and AI solutions to address business problems and improve organizational processes. They are responsible for the end-to-end lifecycle of these solutions, including scoping, validation, production-quality coding, and clear communication of insights to stakeholders.
Design and implement advanced optimization models to improve supply chain performance, cost efficiency, and sustainability. Develop scalable analytical solutions using machine learning and statistical techniques to address complex global supply chain challenges.
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