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LexisNexis Risk Solutions

Data-driven risk assessment & analytics solutions

Lead Data Scientist / Quantitative Analyst - Commodity Intelligence

Data ScienceConfirmed live in the last 24 hours
Full-time€71.6k - €119.4kIn-person

About the Job

Requirements

  • At least 5 years of practical experience in predictive modelling in commodity markets or trading, including supply, demand, and prices.
  • Experience working in a goal-driven team directly with internal and external customers to identify and solve high-value business problems, with the ability to work independently and explain complex concepts simply to stakeholders.
  • Ability to write production-ready code in Python and SQL, and use AI code generation and Spec-Driven Development productively and manageably, with familiarity with common data science and analytics libraries.
  • Experience with data modelling, transformation, and visualization, such as Python Dash.
  • Experience with software development practices including modularization, versioning with Git, testing, and writing understandable code, as well as containerization with Docker and orchestration with Airflow.
  • Knowledge of assumption-based scenario modelling and marginal supply cost curves.
  • A habit of starting simply to gain early buy-in and iterating on feedback to add value.
  • Curiosity and a desire to understand the world.

Responsibilities

  • Create and continuously improve analytical commodity market models in Python, co-developing quantitative models with analysts and engineers, including demand modelling; supply modelling for capacity and cost; storage, trade, and transport modelling; market balance; and market price forecasting.
  • Guide, project-manage, develop, and retain market-modelling talent, and align work and business outcomes with stakeholders.
  • Connect, clean, and impute freight, pricing, and supply-and-demand datasets from diverse internal and external sources, turning raw, imperfect, and incomplete data into actionable market insight.
  • Create interactive analytics, planning, and decision-support tools using data and models, such as Dash by Plotly; develop fast prototypes with Spec-Driven Development; and deliver data and models into the ICIS Data Lakehouse and shared platforms.
  • Discuss models with customers, share the team’s view on market structure, key drivers, and decision support, translate domain knowledge into models, and develop a deep understanding of market operations and decision-making.
  • Work toward goals in a self-organized manner and take project-management responsibility for development work from day one.
  • Guide and support others in model development, implement framework enhancements hands-on, and share components, knowledge, and innovation with peers.

Desired Qualifications

  • Existing knowledge of the chemical industry.
  • Experience with Databricks and Snowflake.

About the Company

LexisNexis Risk Solutions

Data-driven risk assessment & analytics solutions

LexisNexis Risk Solutions provides data, analytics, and decision tools to help organizations assess and manage risk across many industries. Its offerings combine large data sets with advanced analytics to support better decisions, improve operations, and protect consumers. By covering sectors like financial services, government, healthcare, insurance, retail, and public safety, the company helps customers evaluate likelihoods of risk, detect issues, and act more efficiently. The goal is to turn data into actionable insight that reduces risk, increases operational efficiency, and supports compliant, informed decision-making for its clients.

Company size
5,001-10,000
Company stage
Not listed
Total funding
Not listed
Headquarters
Alpharetta, GA
Founded
1997

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