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Sign Up to ReadSenior Data Scientist / Quantitative Analyst - Commodity Global Trade Shipping & Logistics
ICIS – Karlsruhe/Germany or London
About ICIS
ICIS is part of Risk Solutions Group (RSG) a division of RELX Group, a FTSE 20 company with revenues of $12.6 billion in 2025 and an employee base of over 37,000 people. 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 worlds 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, and Tokyo.
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 join 30+ experienced Data Scientists in our Analytics Hubs in Karlsruhe or London. Our Data Science group create forecast models, predictive data and interactive analytical tooling for trading and scenario planning. We model commodity markets with a wide range of techniques from fundamental market modelling, statistical to machine learning & AI, mathematical optimisation / linear programming, system dynamics and agent-based models. We work in small teams with a high degree of ownership and direct collaboration with customers.
In your role, you will primarily focus on creating market-leading predictive models and interactive analytics for Chemicals, the global supply network for petrochemical commodities, recycling materials and their end-use applications. As part of our foundational market data, you will specialize in global trade prices & volumes, shipping & logistics and their impact on global supply & demand. Your work will directly help thousands of users to quantify impacts to their markets.
Key Accountabilities/Responsibilities:
Create and continuously improve analytical commodity market models in Python : Co-develop with our analysts & engineers strong quantitative market models, such as demand modelling, supply modelling for capacity & cost, storage, trade & transport modelling, market balance & market price forecasting. Apply mathematical optimization techniques to logistics and trading-related problems (e.g., routing)
Connect, clean, and impute freight, pricing, and supply/demand datasets from diverse internal and external sources . Turn raw, imperfect and incomplete data into actionable market insight
Create interactive analytics , planning and decision support tools that utilize & visualize data & models (eg Dash by Plotly). Innovate fast prototypes with Spec-Driven-Development. Deliver data and models into ICIS Data Lakehouse and shared platforms.
Discuss models with customers . Share our view on the market structure, key drivers & decision support. Translate gained domain knowledge back into models and build a deep understanding of operation and decision making in our markets
Work goal-driven and self-organized with own project management responsibility on developments from day 1.
Work with data engineers to productionize models and integrate new data sources into the platform
Guide and support others in the development of models as well as create hands-on own implementations of framework enhancements. Actively share components, knowledge & innovation with peers
Key Skills/Experience Required:
Minimum of 3 to 5 years of practical experience in predictive modelling in the context of (commodity) markets or trading, particularly global trade flows, storage, supply chain logistics and their impact on supply, demand and prices. Knowledge of Mathematical/numerical optimization (e.g., linear programming, convex optimization). Ideally also assumption-based scenario modelling and cost curves
Experience to work goal driven directly with internal/external customers to identify & solve high-value business problems, self-organised. Strong communication and engagement, ability to explain complex concepts simply to stakeholders
Production-ready code in Python and SQL , using AI-code generation and Spec-Driven-Development in a productive & manageable way, familiar with common Data Science & analytics libraries
Data modelling, transformation, and visualization (eg Python Dash)
Experience with software development (modularisation, versioning eg with GIT, tests, understandable code), with containerization (Docker) and orchestration (Airflow)
Habit of starting simple first to get buy-in early and iterate on feedback to add value
Curiosity & desire to understand the world
A plus: existing knowledge of the chemical industry, Databricks & Snowflake
Ideally, familiarity with optimization libraries (e.g., Pyomo, SciPy, Gurobi/CPLEX)
Fully remote
RELX
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