Senior Data Scientist & AI Solutions (m/f/d)

ICIS is part of Lexis Nexis Risk 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 passionate about applying data science, AI and analytics to solve complex business problems and create products that customers love?

At ICIS, we're building the next generation of data-driven and AI-powered solutions for global commodity markets. As a Senior Data Scientist, you will work directly with customers, domain experts, product managers and engineers to uncover high-value opportunities, develop innovative solutions, and turn successful customer outcomes into scalable solutions.

This is a key role that will shape the evolution of the organisation. You will apply data science, analytics and AI techniques to create practical, user-focused solutions that solve real-world challenges and help ICIS customers to optimize global resources. You will primarily focus on Chemicals, but experience in Energy, commodities or related industrial sectors is also highly relevant.

Key Accountabilities/Responsibilities

• Work closely with customers to understand their goals, workflows, decision processes and key business challenges.
• Identify high-impact opportunities where data science, analytics and AI can create measurable value.
• Rapidly prototype, systematically test and iterate solutions with customers, incorporating user feedback to improve value, usability and adoption.
• Apply data science, machine learning and AI techniques, including modern generative AI and agentic approaches where appropriate, to solve customer problems.
• Combine ICIS data, domain expertise and customer context to develop differentiated analytical solutions.
• Communicate insights, recommendations and technical concepts clearly to both technical and non-technical audiences.
• Contribute to best practices in experimentation, model development, evaluation, documentation and maintainability.
• Surface customer needs and gaps in data, semantics and platform capabilities to help shape future ICIS product, data and AI investments.
• Collaborate with product managers, subject matter experts, engineers and commercial stakeholders in a cross-functional Customer Deployed Team.
• Share learnings across teams to accelerate innovation and improve future customer engagements.

• 3-5 years of experience in Data Science, Applied AI, Analytics or a related field.
• Proven track record of developing and delivering analytical, machine learning or AI solutions from concept through deployment.
• Experience evaluating and applying modern AI approaches, including large language models, retrieval-based systems and agentic workflows.
• Strong Python skills and experience with common data science and analytics libraries.
• Strong problem-solving skills and ability to work effectively in ambiguous and rapidly evolving environments.
• Experience designing experiments and measuring business impact of data science solutions.
• Good understanding of data modelling, data quality and working with structured and unstructured data.
• Experience with cloud platforms, APIs and containerised applications.
• Professional use of version control and collaborative software-development practices.
• Experience working directly with business stakeholders or customers to identify and solve high-value business problems.
• Excellent communication and stakeholder management skills with the ability to translate business challenges into practical analytical solutions.
• Experience in Chemicals, Energy, commodity markets or related industrial sectors is desirable but not required

• Work on Problems That Matter: global organizations make better decisions using data, analytics and AI
• Build the Future of AI in commodity markets: Play a key role in shaping next-generation AI products and capabilities that will influence the future of our business and our industry
• Work with Exceptional People: Join a multidisciplinary team of data scientists, engineers, economists, industry experts and product leaders who are passionate about innovation and customer impact
• Enjoy Great Benefits: e.g. fitness studio, 20 days work from anywhere and 2 days additional leave for social engagement and ongoing learning and professional development opportunities

Our Data Science team combines the energy of a start-up with the support and stability of a global organization of more than 37,000 employees. In 2024, our Data Science team achieved an Employee Net Promoter Score (eNPS) of 81, reflecting a highly engaged and supportive culture.

ICIS is committed to building an inclusive workplace where everyone can thrive. We welcome applications from people of all backgrounds, experiences and perspectives. We believe diverse teams create better products, make better decisions and drive greater innovation. If you're excited about this opportunity but don't meet every requirement, we encourage you to apply.

Primary Location Base Pay Range: Germany - Karlsruhe €59,300 - €98,600.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.