841 Data Scientist jobs available for remote work from home. Apply for positions such as Alternance – Data Scientist Big Data & Intelligence Artificielle (H/F), Lead Data Scientist, Data Scientist – Agentic AI - Permanent UK and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Data Scientist will collect, clean, and structure large volumes of data while designing and training machine learning models. They will also develop AI solutions, implement Big Data pipelines, and create data visualization dashboards to support business and IT teams.
You will design and develop statistical models for property price adjustments and build spatial algorithms to capture local market dynamics. Additionally, you will implement recommendation systems, integrate LLM-based services, and maintain production APIs while collaborating with frontend engineers.
Design and deliver production-grade multi-agent systems and AI services for enterprise-scale clients. Implement robust RAG pipelines, agent memory management, and AgenticOps practices to ensure reliable and ethical AI operations.
Design, build, and deploy scalable machine learning models and data products to support enterprise initiatives. Collaborate with engineering and product teams to integrate these solutions into production environments using cloud platforms.
The Staff Data Scientist will lead the design and scaling of causal measurement and personalization systems to optimize marketplace performance and user value. They will drive high-impact modeling initiatives, mentor senior team members, and partner with cross-functional leaders to align data science strategy with business goals.
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The Research Data Scientist will lead the development and application of computational and statistical methods, including AI and machine learning, to analyze biomedical data. They will also manage database-to-deployment pipelines and communicate scientific findings through publications and conferences.
The Senior Data Scientist will develop and deploy advanced machine learning and computer vision solutions using Azure. They will collaborate with data engineers to build scalable pipelines and communicate insights to stakeholders.
Design, develop, and deploy AI and machine learning models using advanced cloud frameworks and services. Collaborate with cross-functional teams to integrate scalable AI solutions into business applications.
Develop and advance machine learning models to optimize healthcare claim audits and improve financial outcomes. Create technical frameworks and data pipelines to enhance team efficiency and model precision.
The role involves collaborating with data science and engineering stakeholders to onboard new workflows and maintain the experimentation platform. Responsibilities also include designing and operating methodologies, maintaining data pipelines, and developing new tools for experimentation needs.
The Senior Data Scientist will design and deploy advanced machine learning systems for device identification and fraud prevention. They will also contribute to the development of scalable data pipelines and collaborate with cross-functional teams.
The Senior Data Scientist will apply analytical methods to solve business problems and design end-to-end analytical solutions. They will also communicate results and recommendations clearly to stakeholders.
The Senior Data Scientist will apply analytical methods to solve business problems and design end-to-end analytical solutions. They will also communicate results and recommendations clearly to stakeholders.
The Senior Data Scientist will apply analytical methods to solve business problems and design end-to-end analytical solutions. They will also communicate insights and recommendations to stakeholders across the organization.
The Lead Data Scientist will own the science by designing and leading experimentation programs like A/B tests and causal inference studies that inform product and go-to-market decisions. They will also build and deploy predictive models for business forecasting and lead and mentor a team of analysts and data scientists.
The role involves designing and analyzing experimental tests to measure advertising incrementality and building causal and marketing mix models for multi-channel attribution. Key tasks include developing and productionizing scalable data pipelines for event-level data ingestion and ensuring measurement datasets are clean and privacy-compliant.
The role involves driving product and business impact through statistical modeling, experiment design, and classifier implementation across search engine, AI, and revenue optimization functions. Responsibilities also include owning key data pipeline pieces, resolving data integrity issues, and implementing derived data features for internal users.
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This role involves owning the end-to-end development of data-driven solutions on the RiskOS platform, spanning data exploration, modeling (including Generative AI agent design), production deployment, and monitoring. The Staff Data Scientist will leverage expertise in fraud/risk management to develop detection models and integrate LLM-powered tools to enhance analytics and workflows.
The role involves designing, optimizing, and maintaining scalable ETL pipelines using PySpark and Databricks on cloud platforms, alongside developing automated data validation processes for quality checks. Responsibilities also include building and tuning ML/AI and optimization models, engaging with business stakeholders, and collaborating with cross-functional teams.
The Data Scientist will build predictive models using scientific computing and statistical methods to locate ore-forming processes and predict mineralization in 2D and 3D, while helping to build a worldwide dataset with careful uncertainty quantification. They will create models and develop software to accelerate critical battery metal discovery, working closely with geoscientists to guide exploration and field programs.
The Data Scientist will build predictive models using scientific computing and statistical methods to locate evidence of ore-forming processes and predict mineralization locations in 2D and 3D. They will also help build a worldwide dataset, create models, and develop software to accelerate the discovery of critical battery metals.
The role involves designing, implementing, and maintaining robust data pipelines, processing data via APIs, and developing reporting layers like dashboards and automated reports. Key tasks include building predictive and optimization models for areas such as player lifetime value and churn prediction, and applying state-of-the-art AI/ML techniques.
The role involves working on an intelligent matching project between doctors and pharmaceutical products, requiring technical evolution towards Generative AI and LLMs. Responsibilities include developing and maintaining data pipelines and applying classical Machine Learning techniques.
The role involves setting the direction for the data science function, owning company-wide metric strategy, and leading the experimentation framework and standards across product squads. This person will also drive strategic opportunity sizing and own the predictive modeling and machine learning work for the company.
The role involves continuously improving existing machine learning models by incorporating new features and parameters, and developing scalable supervised and unsupervised learning algorithms in collaboration with the Machine Learning Engineering team. Responsibilities also include exploring new data sources, researching innovative ML solutions to optimize the value chain, and regularly conducting and evaluating A/B tests.
The role involves analyzing enterprise processes to identify automation opportunities and designing/implementing AI strategies using GenAI and agentic systems to optimize operations across domains like procurement and inventory. Key tasks include developing architecture mappings and translating business needs into actionable, scalable AI solutions.
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As a Data Scientist, responsibilities include executing ambitious client transformation projects through data and collaborating across divisions like Activation, Creativity, and Strategy to deliver integrated services. The role involves developing strong client relationships by applying technical skills to aid in the transformation of their marketing departments.
The role involves developing and deploying production-grade AI systems, including building scalable APIs for ML models and owning the end-to-end delivery of AI solutions. Key tasks include designing advanced AI architectures like RAG systems and optimizing model performance for latency and cost efficiency at scale.
This role involves owning complex forecasting challenges directly impacting supply chain, marketing spend, and overall business growth, requiring the development of advanced demand forecasting models and marketing spend optimization algorithms. Key tasks include building experimentation frameworks for incrementality testing and developing marketing attribution models for complex customer journeys.
The Staff Data Scientist will take deep ownership of high-impact problem spaces within advertising, specializing in measurement, identity, and signal quality, influencing strategic direction and setting a high technical bar. Key tasks include developing identity resolution models, advancing lift methodologies and experimentation, maximizing signal value for predictive performance, and defining ground truth evaluation frameworks.
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