Data scientist h/f

GEODIS est un leader mondial du transport et de la logistique, reconnu pour son expertise sur l'ensemble de la supply chain. Partenaire de croissance de ses clients, GEODIS intervient sur cinq métiers : l'optimisation de la chaîne d'approvisionnement, le Freight Forwarding, la logistique contractuelle, la distribution & l'express et le transport routier. Avec un réseau mondial couvrant près de 166 pays et plus de 49 720 collaborateurs, GEODIS se classe au sixième rang mondial de son secteur. En 2024, GEODIS a réalisé un chiffre d'affaires de 11,3 milliards d'Euros. GEODIS est une société du groupe SNCF.
A compétences égales, une attention particulière sera accordée aux candidatures des personnes en situation de handicap. We are seeking a talented Data Scientist to join our Sales Performance team. The ideal candidate will BE responsible for developing predictive models and managing Master Data Management (MDM) governance. This role requires a strong analytical mindset and the ability to work collaboratively within a dynamic sales environment.

Key Responsibilities :

1°) Predictive Modeling :
Develop and implement predictive models to enhance sales performance and forecasting.
Analyze large datasets to identify trends, patterns, and insights that drive business growth.
Collaborate with sales and marketing teams to translate business needs into data-driven solutions.

2°) MDM Governance :
Oversee the governance of Master Data Management processes to ensure data accuracy and integrity.
Work with cross-functional teams to establish and enforce data management best practices.
Monitor and improve data quality by implementing data cleansing and validation processes.
Animate a data steward community.

3°) Data Analysis and Reporting :
Generate reports and visualizations to communicate insights and recommendations to stakeholders.
Utilize statistical and machine learning techniques to drive data-driven decision-making.

4°) Collaboration and Communication :
Collaborate with IT and data engineering teams to ensure seamless data integration and access.
Present findings and insights to both technical and non-technical audiences.