Data Scientist Dynamic Pricing & Forecasting - Freelance
Forecasting price indices and building decision-support dashboards for commercial teams. Developed forecasting models and packages, optimized pricing strategies, and integrated exogenous variables.
About this role
Within ArcelorMittal's CMO department, the Data Science team is responsible for developing models that help commercial teams optimize the prices offered to clients, and for building intelligent dashboards to support business decision-making.
In this context, I was responsible for the dashboard dedicated to forecasting future prices based on market indices. This dashboard integrates three-month forecasts, providing strategic support to the commercial teams on a daily basis.
I also developed a forecasting package that enables easy comparison and testing of different models, parameter optimization, and the integration of exogenous variables from various sources. This package is currently in production and its results are used daily by end users.
In addition, I contributed to the maintenance and development of the dynamic pricing tool used by commercial teams. A recurring part of the role involved translating business needs into concrete technical solutions through regular workshops with stakeholders.
Key contributions
- Built and maintained a forecasting dashboard providing 3-month market index predictions to support commercial teams.
- Developed an internal forecasting package enabling easy model comparison, parameter tuning, and integration of exogenous variables — deployed in production.
- Contributed to the dynamic pricing tool used by commercial teams to optimize client pricing.
- Facilitated regular workshops with business stakeholders to align technical developments with operational needs.