841 Data Scientist jobs available for remote work from home. Apply for positions such as Senior/Staff Data Scientist, Data Scientist II, Senior Data Scientist ID80052 and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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You will own end-to-end data analysis, experimentation, and forecasting to drive product and risk decision-making. You will also partner with machine learning engineers to evaluate model performance and establish measurement frameworks for business impact.
You will own end-to-end data analyses, including framing questions, defining success metrics, and running experiments to improve job seeker relevance. Additionally, you will partner with product and engineering teams to inform strategy and mentor other data scientists on best practices.
The Senior Data Scientist will develop, deploy, and maintain production machine learning models within a cloud-native environment. They will also build data pipelines and collaborate with cross-functional teams to deliver scalable AI and ML solutions.
The Senior Data Scientist will independently scope and deliver end-to-end data science projects, including model development, validation, and productionization. They will also partner with engineering teams to deploy models and provide data-driven recommendations to senior leadership.
You will own the intersection of predictive decision-making and engineering by developing and optimizing AI-driven decision engines for retail operations. This involves collaborating with the engineering team to maintain high model accuracy and scalable software solutions.
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You will design and analyze A/B tests to measure the impact of machine learning models on key business metrics like revenue and conversion. Additionally, you will develop and improve search, ranking, and personalization algorithms while communicating insights to technical and business stakeholders.
You will design measurement frameworks and marketplace tools to balance competing demands on Netflix's discovery surfaces. Additionally, you will partner with product and engineering teams to define metrics and drive research from concept to implementation.
You will own the end-to-end data science lifecycle, including model development, P&L reconstruction, and financial forecasting for the oil and gas sector. The role involves collaborating directly with traders and finance teams to turn complex business problems into actionable research plans.
You will prototype, evaluate, and maintain machine learning models for fraud detection while designing experiments to measure the impact of interventions. Additionally, you will collaborate with cross-functional teams to translate model outputs into real-world mitigations and build anomaly detection systems.
The Senior Data Scientist will drive statistical execution and algorithmic validation of Meridian MMM frameworks to provide multi-objective spend recommendations. They will also collaborate with cross-functional engineering teams to resolve pipeline requirements and perform data transformations.
The Senior Data Scientist will lead the end-to-end model development lifecycle, including problem definition, feature engineering, and deployment of predictive models. They will also build cross-functional partnerships to identify use cases that enhance operational efficiency and drive business value.
The Senior Data Scientist will develop and define analytical best practices to generate strategic insights and actionable research using internal and external data. They will own end-to-end machine learning model development and collaborate with cross-functional teams to optimize fleet, pricing, and ridesharing products.
You will define the technical direction for analytics and modeling to improve robot performance, reliability, and unit economics. This involves transforming massive volumes of complex robot data into actionable insights across hardware, software, and manufacturing operations.
The Senior Data Scientist will create strategic solutions by analyzing large datasets and interpreting results for stakeholders. They are responsible for leading data-driven projects, ensuring psychometric rigor, and communicating actionable insights to cross-functional teams.
The Data Scientist will develop and scale analytical capabilities, including predictive and machine learning models, to improve client decision-making and drug management solutions. They will collaborate with cross-functional teams to analyze complex healthcare data sets and communicate actionable insights to stakeholders.
The Data Scientist will develop and scale analytical capabilities, including predictive and machine learning models, to improve client decision-making and drug management solutions. They will analyze complex pharmacy and medical claims data to identify trends and communicate actionable insights to both technical and non-technical stakeholders.
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The Senior Data Scientist will guide the implementation of ethical AI and machine learning solutions to solve complex business problems for strategic customers. They will lead data acquisition, model development, and cross-functional collaboration to ensure high-quality, scalable, and transparent AI deployments.
Design, build, and maintain predictive models to forecast member demand, care utilization, and provider network capacity. Collaborate with cross-functional teams to translate data insights into actionable business recommendations.
The Data Scientist will design and own machine learning solutions from scratch using unstructured and incomplete enterprise datasets. They will be responsible for applying research-minded problem-solving to complex tasks like risk scoring, fraud detection, and claim severity modeling.
You will be responsible for developing, deploying, and maintaining production machine learning models within a cloud environment. Additionally, you will collaborate with cross-functional teams to build scalable data pipelines and support data-driven decision-making.
You will drive inventive transformation by blending strategic, creative, and scientific capabilities to deliver cutting-edge solutions for clients. This involves building and deploying advanced AI models, including LLMs and agentic applications, while ensuring robust MLOps practices.
Develop and implement ML/NLP models while collaborating with stakeholders to deliver data-driven business solutions. Assist in deploying models using MLOps practices and contribute to the creation of ML assets.
Lead the design, development, and implementation of ML/NLP models while ensuring data quality and security compliance. Collaborate with stakeholders to deliver scalable solutions and drive ML asset creation using advanced MLOps practices.
The role involves building predictive models and dashboards to optimize user acquisition, retention, and lifetime value within the marketing and growth function. You will apply causal inference and experimentation techniques to measure the incremental impact of marketing investments and promotions.
Own the analysis and algorithmic solution of technical problems in ads delivery, translating them into production-ready ML models. Partner cross-functionally to deploy high-availability microservices and establish robust monitoring and lineage tracking for ML systems.
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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 delivery of iterative, high-impact technical approaches.
Transform operational and performance data into executive-level visualizations, dashboards, and analytical narratives to support decision-making. Develop robust analytical models and standardized reporting artifacts to enhance situational awareness across a federal IT environment.
Develop and deploy cutting-edge machine learning models to solve complex business problems in Physical AI and infrastructure. Collaborate with cross-functional teams to integrate scalable solutions and mentor junior data scientists.
Lead the development of predictive statistical models to forecast product demand and provide analytical insights for business decisions. Collaborate with cross-functional partners in finance and operations to ensure data model quality and align demand schedules.
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