The Role<ul><li>The Data Scientist will play a pivotal role in partnering with commodity subject matter experts to develop new forecasts and data sets, while also transforming the company’s existing commodity price forecasting and benchmarking capabilities into scalable, efficient solutions using Python, R, and other advanced analytics platforms. This role is central to enhancing the accuracy, agility, efficiency and transparency of forecasting processes. The Data Scientist will also lead the integration of artificial intelligence and machine learning techniques to uncover patterns, improve predictive performance, increase automation and efficiency, and develop new products and tools. By bridging traditional methods with new technologies, the Data Scientist will help drive innovation and operational excellence in a data-driven environment. Key metrics for success in this position include delivering timely updates to forecasting models and data products, ensuring measurable improvements in forecast accuracy for key commodity benchmarks and successfully deploying AI-powered analytics tools with minimal issues, while maintaining strong stakeholder engagement and communication.The ideal candidate will thrive in a fast-paced and innovative environment, have a can-do attitude,  and can juggle a wide variety of tasks and projects.</li></ul>Principal accountabilities<ul><li>Modernize Forecasting Models – Support rebuilding and enhancing existing Excel-based commodity price forecasting models using Python, R, or other advanced analytics tools to improve scalability, maintainability, and performance.</li><li>Develop New Models and Analysis – Develop new forecasts and related data sets that drive business insights and supports decision-making for Fastmarkets clients.</li><li>Integrate Artificial Intelligence - Design and implement AI and machine learning models, including generative AI and LLMs to enhance forecasting accuracy, automate insight generation, develop intelligent data products, and create conversational analytics interfaces, such as Chatbots and Agents.</li><li>Data Pipeline Development - Develop robust data pipelines to ingest, clean, and transform large datasets from internal and external sources for use in forecasting and cost benchmarking models.</li><li>Model Validation and Performance Monitoring - Establish validation frameworks and performance metrics to ensure model reliability and transparency.</li><li>Stakeholder Collaboration - Partner with commodity subject matter experts to understand their forecasting processes and techniques, translate them into intuitive technical solutions, and communicate insights effectively.</li><li>Support Analytics Product Development – Develop new and innovative data products that complement forecast models to drive business insights and supports decision-making for Fastmarkets clients.</li><li>Documentation and Knowledge Sharing - Maintain clear documentation of models, methodologies, and assumptions, and contribute to a culture of continuous learning and innovation.</li></ul>Key interfacesThe Data Scientist is a critical member of Fastmarkets Analytics, a global team of 90+ analysts, economists and engineers at Fastmarkets that produce commodity forecasts, cost and emissions benchmarking, and related data.<ul><li>Partner with Analysts and Economists to translate commodity market expertise into robust, data-driven forecasting and benchmarking models.</li><li>Collaborate closely with the Technology and Data Operations teams, including full stack and data engineers, to ensure seamless integration of data pipelines, scalable infrastructure for model deployment, and alignment on data governance and quality standards.</li><li>Partner with data scientists across Fastmarkets to align methodologies, share domain-specific insights, and co-develop scalable models that support enterprise-wide analytics initiatives and foster a unified data strategy.</li><li>Partner with the Product team to translate customer needs into data-driven features and functionality, ensuring that new data products align with market requirements and deliver measurable value to B2B clients.</li></ul>

Our price data, forecasts, and market analyses give our customers a strategic advantage in complex, volatile and often opaque markets. Our events provide immersive experiences to network, trade and discuss the critical issues of the day.
Lithium Hangar Holdco Limited is the ultimate holding company for the Fastmarkets group of companies. Lithium Hangar Holdco Limited (14476245) is a company registered in England and Wales and is controlled by funds managed and/or advised by Astorg. Astorg is a European private equity firm with over &euro;20 billion of assets under management.

Data Scientist (Hybrid)

The Role<ul><li>The Data Scientist will play a pivotal role in partnering with commodity subject matter experts to develop new forecasts and data sets, while also transforming the company’s existing commodity price forecasting and benchmarking capabilities into scalable, efficient solutions using Python, R, and other advanced analytics platforms. This role is central to enhancing the accuracy, agility, efficiency and transparency of forecasting processes. The Data Scientist will also lead the integration of artificial intelligence and machine learning techniques to uncover patterns, improve predictive performance, increase automation and efficiency, and develop new products and tools. By bridging traditional methods with new technologies, the Data Scientist will help drive innovation and operational excellence in a data-driven environment. Key metrics for success in this position include delivering timely updates to forecasting models and data products, ensuring measurable improvements in forecast accuracy for key commodity benchmarks and successfully deploying AI-powered analytics tools with minimal issues, while maintaining strong stakeholder engagement and communication.The ideal candidate will thrive in a fast-paced and innovative environment, have a can-do attitude,&nbsp; and can juggle a wide variety of tasks and projects.</li></ul>Principal accountabilities<ul><li>Modernize Forecasting Models – Support rebuilding and enhancing existing Excel-based commodity price forecasting models using Python, R, or other advanced analytics tools to improve scalability, maintainability, and performance.</li><li>Develop New Models and Analysis – Develop new forecasts and related data sets that drive business insights and supports decision-making for Fastmarkets clients.</li><li>Integrate Artificial Intelligence - Design and implement AI and machine learning models, including generative AI and LLMs to enhance forecasting accuracy, automate insight generation, develop intelligent data products, and create conversational analytics interfaces, such as Chatbots and Agents.</li><li>Data Pipeline Development - Develop robust data pipelines to ingest, clean, and transform large datasets from internal and external sources for use in forecasting and cost benchmarking models.</li><li>Model Validation and Performance Monitoring - Establish validation frameworks and performance metrics to ensure model reliability and transparency.</li><li>Stakeholder Collaboration - Partner with commodity subject matter experts to understand their forecasting processes and techniques, translate them into intuitive technical solutions, and communicate insights effectively.</li><li>Support Analytics Product Development – Develop new and innovative data products that complement forecast models to drive business insights and supports decision-making for Fastmarkets clients.</li><li>Documentation and Knowledge Sharing - Maintain clear documentation of models, methodologies, and assumptions, and contribute to a culture of continuous learning and innovation.</li></ul>Key interfacesThe Data Scientist is a critical member of Fastmarkets Analytics, a global team of 90+ analysts, economists and engineers at Fastmarkets that produce commodity forecasts, cost and emissions benchmarking, and related data.<ul><li>Partner with Analysts and Economists to translate commodity market expertise into robust, data-driven forecasting and benchmarking models.</li><li>Collaborate closely with the Technology and Data Operations teams, including full stack and data engineers, to ensure seamless integration of data pipelines, scalable infrastructure for model deployment, and alignment on data governance and quality standards.</li><li>Partner with data scientists across Fastmarkets to align methodologies, share domain-specific insights, and co-develop scalable models that support enterprise-wide analytics initiatives and foster a unified data strategy.</li><li>Partner with the Product team to translate customer needs into data-driven features and functionality, ensuring that new data products align with market requirements and deliver measurable value to B2B clients.</li></ul>

Data Scientist (Hybrid)

About the Job

About the Company

Fastmarkets Ltd

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