Growth Data Scientist
Pubblicato il 03-10-2026 - Edenred in Monza
Overview
In this role you will design, develop and deploy advanced analytics and ML solutions to support sales and customer management. You will translate data insights into actionable outputs, partnering with stakeholders to embed models into operational processes. The role blends model development with practical application in a hybrid environment, contributing to a data-driven strategy and business impact. You will be part of a multinational team that values meritocracy and continuous growth, tackling diverse data challenges at scale.
Retribuzione / Benefits
Smart-working (10 days/month)
Buoni pasto
Welfare Plan
Comprehensive health benefits including supplementary medical insurance, accident protection and life coverage
Responsabilità
Design, develop and deploy ML and advanced analytics models
Build predictive models (e.g., churn, cross-sell, propensity) and develop features/datasets
Translate models into operational outputs (lists, scores, targeting logics) to support commercial processes
Collaborate with business stakeholders to translate requirements into data-driven solutions
Monitor model performance and business impact; contribute to test-and-learn approach
Present insights and strategic recommendations to management
Coordinate with Data Engineering and IT for data quality, governance and availability
Contribute to evolution of the company's data-driven strategy
Requisiti fondamentali
3/5 years of experience in Data Scientist roles, preferably in Sales or Customer Analytics
Strong knowledge of Python, PySpark, SQL and major ML libraries (scikit-learn, XGBoost, TensorFlow or similar)
Hands on experience with Azure Databricks (Workflows and Job Orchestration) and familiarity with Azure ecosystem (Azure ML, Azure DevOps, Azure Data Factory)
Practical experience with end-to-end predictive modelling projects (propensity, churn, segmentation)
Ability to work with complex/incomplete datasets
Understanding of data architectures and ETL/ELT pipelines for data prep and transformation
Degree in a scientific or quantitative discipline
Fluent English
Excellent stakeholder management and communication skills
Strong storytelling and presentation skills for technical and non-technical audiences
Ability to translate models and analyses into actionable business outputs
stakeholder management
communication
storytelling
Python
PySpark
SQL