Senior Data Scientist (Commodity Markets) m/f/d

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About ICIS ICIS is part of Lexis Nexis Risk a division of RELX Group, a FTSE 20 company with revenues of $12.9 billion in 2025 and an employee base of over 30,000 people across 40 countries. ICIS makes some of the world's most important markets more trusted and predictable by providing data services, thought leadership and decision tools. We exist to help businesses in the energy, petrochemical and fertilizer industries make strategic decisions, mitigate risk, improve productivity, and capitalise on new opportunities. Thousands of decisions are taken across supply chains every day using our intelligence and we make this possible through a global presence that delivers the targeted, local insights customers need to achieve growth in this new world of meaningful data. Shaping the world by connecting markets to optimise the world's valuable resources. With a global team of more than 700, ICIS has employees based in London, New York, Houston, Karlsruhe, Frankfurt, Milan, Mumbai, Singapore, Guangzhou, Beijing, Shanghai, Dubai, Sao Paulo, Seoul, Tokyo and Perth. Job Purpose: Are you an experienced Quant Analyst / Data Scientist in energy markets? As Quantitative Analyst at ICIS, you will drive data-based innovation and complement our technical capability to operationally deploy and maintain Data Science models and model interfaces in some of the largest industries in the world - energy and chemicals with global supply networks. You will join our existing team of experienced Data Scientists and work closely alongside ICIS market experts around the globe. Our models enable the analysis of prices and market fundamentals to support decision making in trading and operations. You will be part of an international team, which requires occasional travel globally. As of day one, you will take responsibility in demanding analytics innovation projects - your primary focus will be to design, improve and maintain models and Python (dash) applications for augmented energy pricing processes across a wide range of markets. Key Accountabilities/Responsibilities: Maintain and enhance applications in Python (Dash) to put the "human in the loop" with Data Science models Drive and support R&D and operation of data-driven analytical market models: Together with our analysts and market experts, you will co-develop strong quantitative market models to predict key market variables drawing from a wide variety of techniques; guide and support others in the development of models, implement new models as well as model enhancements, such as driving cloud-based model and process automation Engage with internal market experts to explain our models and insights and to discuss the market structure and key drivers - translating domain knowledge back into our models and building a deep understanding of operations and decision making in our markets Drive maintenance and improvements of the code base and code structure for operational models and backend data architectures Develop, test, and roll out new application functionality and change requests following product owner prioritization Manage operational models & applications (monitoring, refactoring, update of live services) Review and debug code and ensure good code documentation Enable efficient communication across teams through fast prototyping and demos of potential solutions Expand your knowledge, by learning new techniques and applying them to existing and new analytical problems in our markets. Actively share knowledge and innovation areas with your peers Key Skills/Experience Required: Minimum of 3 to 5 years of practical experience as a software engineer, preferably in the context of markets and market prices Excellent Python skills and experience with Python packages for applications (such as Dash) Professional use of version control tools in projects involving several developers Experience with designing and managing containerized applications and familiarity with cloud platforms (e.g. AWS) Data handling and data modeling knowledge and experience using relational databases (e.g. PostgreSQL) Holistic perspective on business value from analytics and a strong ability to explain complex topics to diverse stakeholders at the appropriate level, strong communication and engagement Preferably previous exposure to Data Analytics or Data Science and an interest in working on analytics and forecasting projects heavily reliant on human / machine collaboration

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