Leveraging data to drive strategic decisions and optimize business outcomes at Capgemini Engineering.
Requirements
- Minimum of 6 years of professional experience in advanced analytics, statistical modeling, or machine learning, including at least 3 years in a dedicated Data Scientist role.
- Proficient in Python and its data science ecosystem (e.g., scikit-learn, pandas, NumPy, TensorFlow, PyTorch).
- Strong foundation in mathematics, probability, and statistics.
- Hands-on experience with cloud-based data science platforms and services (AWS preferred; GCP or Azure also valued).
- Proven track record of working with complex, real-world datasets to deliver measurable business value (e.g., cost reduction, revenue growth, operational efficiency).
- Experience working in Agile or cross-functional product teams.
Responsibilities
- Develop, validate, and deploy statistical and machine learning models to address business challenges such as demand forecasting, optimization, pricing, and customer behavior analysis.
- Source, prepare, and analyze structured and unstructured datasets, ensuring data quality for modeling purposes.
- Monitor and evaluate model performance, refining models through experimentation and iteration.
- Communicate insights effectively through visualizations, reports, and presentations that support decision-making.
- Contribute to the development of standards and best practices for data science workflows, including model evaluation and deployment.
- Stay up to date with advancements in machine learning, statistics, and AI, and apply innovative techniques where relevant.
Other
- Excellent problem-solving and communication skills, with the ability to translate technical findings into actionable insights for non-technical stakeholders.
- Join a multicultural and inclusive team environment.
- Enjoy a supportive atmosphere promoting work-life balance.
- Hybrid work.
- Your career growth is central to our mission.
