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LexisNexis Risk Solutions

Data-driven risk assessment & analytics solutions

Senior Data Scientist / Quantitative Analyst - Commodity Global Trade Shipping & Logistics

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

About the Job

Requirements

  • At least 3 to 5 years of practical experience in predictive modelling in commodity markets or trading, particularly global trade flows, storage, supply chain logistics, and their effects on supply, demand, and prices.
  • Knowledge of mathematical or numerical optimization, such as linear programming or convex optimization.
  • Experience working in a goal-driven, self-organized way with internal or external customers to identify and solve high-value business problems.
  • Ability to explain complex concepts simply to stakeholders.
  • Ability to write production-ready Python and SQL code, use AI code generation and Spec-Driven Development productively and manageably, and work 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.
  • Experience with containerization using Docker and orchestration using Airflow.
  • Ability to start with simple solutions, gain early buy-in, and iterate on feedback.

Responsibilities

  • Create and continuously improve analytical commodity market models in Python, co-developing quantitative models with analysts and engineers, including demand, capacity and cost supply, storage, trade and transport, market balance, and market price forecasting models.
  • Apply mathematical optimization techniques to logistics and trading problems, such as routing.
  • Connect, clean, and impute freight, pricing, and supply-and-demand datasets from diverse internal and external sources, turning imperfect and incomplete data into actionable market insight.
  • Create interactive analytics, planning, and decision-support tools that use and visualize data and models, including tools such as Dash by Plotly.
  • Develop rapid prototypes using Spec-Driven Development and deliver data and models into the ICIS Data Lakehouse and shared platforms.
  • Discuss models with customers, explain market structure, key drivers, and decision support, and translate domain knowledge gained into models while developing a deep understanding of market operations and decision-making.
  • Manage development projects independently from day one.
  • Work with data engineers to productionize models and integrate new data sources into the platform.
  • Guide and support others in model development, implement framework enhancements hands-on, and share components, knowledge, and innovations with peers.

Desired Qualifications

  • Experience with assumption-based scenario modelling and cost curves.
  • Knowledge of the chemical industry.
  • Experience with Databricks and Snowflake.
  • Familiarity with optimization libraries such as Pyomo, SciPy, Gurobi, or CPLEX.

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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