Lead Data Scientist — Global Commodity Market AI & Forecasts

RELX International; United States; Hybrid; USD 80,000 - 133,000; Full time

Job summary

ICIS, part of RELX Group, seeks a Lead Data Scientist to shape predictive models for global commodity markets from Karlsruhe or London. You will build data-driven analytics and interactive tools (Dash) and lead a small data science team in collaboration with engineers, economists and product leaders.

You will apply AI/ML approaches, manage data pipelines, and deliver scalable solutions while working closely with customers and stakeholders in a fast-paced environment.

Qualifications

• Minimum of 5 years of practical experience in predictive modelling in commodity markets or trading.
• Experience with assumption-based scenario modelling and marginal cost curves.
• Ability to work with customers to identify and solve high-value problems.
• Production-ready code in Python and SQL; familiarity with Dash and data libraries.
• Experience in software development practices: modularity, versioning (Git), tests, containers (Docker), and orchestration (Airflow).

Responsibilities

• Create and continuously improve analytical commodity market models in Python.
• Guide, project-manage and develop market modelling talent with stakeholder alignment.
• Connect, clean, and impute freight, pricing, and supply/demand data from diverse sources.
• Create interactive analytics and decision-support tools using data and models (Dash).
• Translate domain knowledge into models and share components with peers.

Skills

Predictive modelling

Python

SQL

Data visualization

Dash/Plotly

Team leadership

Communication

Tools

Docker

Airflow

Git

Databricks

Snowflake

Job description

ICIS, part of RELX Group, seeks a Lead Data Scientist to shape predictive models for global commodity markets from Karlsruhe or London. You will build data-driven analytics and interactive tools (Dash) and lead a small data science team in collaboration with engineers, economists and product leaders.

You will apply AI/ML approaches, manage data pipelines, and deliver scalable solutions while working closely with customers and stakeholders in a fast-paced environment.