Data Scientist

SoTalent; Boulogne-Billancourt; On-site; EUR 60,000 - 90,000; Full time

Job summary

Sotalent in Île-de-France is seeking an experienced Data Scientist to develop and deploy ML/AI solutions within a multidisciplinary data team in the insurance sector.

The role spans the full data science lifecycle, from identifying business use cases to deploying models, with projects covering customer experience, distribution, operational efficiency, fraud prevention and process improvement.

Qualifications

• Master's degree in Data Science, AI, ML, Engineering or related field.
• At least three years of experience as a Data Scientist.
• Experience taking ML models through industrialisation and production deployment.
• Knowledge of ML, predictive modelling, NLP and MLOps.
• Experience or interest in generative AI and LLMs is an advantage.

Responsibilities

• Identify business challenges and opportunities for data science and AI applications.
• Collect, explore and analyse data to support business requirements.
• Design, develop and improve machine learning and predictive modelling solutions.
• Contribute to the industrialisation and production deployment of models using MLOps practices.
• Work on NLP and generative AI applications.
• Integrate data science solutions into business processes and tools.
• Ensure models meet development, security and compliance standards.
• Support effective, strategic and secure data management.
• Monitor developments in data science and AI.
• Collaborate with business stakeholders to promote data-driven decision-making.

Skills

Python

SQL

GitLab

MLOps

NLP

ML

Generative AI

LLMs

Predictive modelling

Education

Master's degree (Bac+5) in Data Science / AI / ML / Engineering

Tools

GitLab

Job description

Job Type: Permanent, Full-time

Industry: Insurance, Data Science, Artificial Intelligence

About the Role

An opportunity is available for an experienced Data Scientist to develop and deploy machine learning and AI solutions within a multidisciplinary data team in the insurance sector.

The role covers the full data science lifecycle, from identifying business use cases and analysing data to developing, industrialising and deploying models. Projects span customer experience, distribution, operational efficiency, fraud prevention and process optimisation.

Key Responsibilities

• Identify business challenges and opportunities for data science and AI applications.
• Collect, explore and analyse data to support business requirements.
• Design, develop and improve machine learning and predictive modelling solutions.
• Contribute to the industrialisation and production deployment of models using MLOps practices.
• Work on natural language processing (NLP) and generative AI applications.
• Integrate data science solutions into business processes and tools.
• Ensure models meet development, security and compliance standards.
• Support effective, strategic and secure data management.
• Monitor developments in data science and artificial intelligence.
• Collaborate with business stakeholders to support adoption of AI solutions and promote data-driven decision‑making.

Requirements

• Master's degree (Bac+5) in Data Science, Artificial Intelligence, Machine Learning, Engineering or a related field.
• At least three years of experience working as a Data Scientist.
• Experience taking machine learning models through industrialisation and production deployment.
• Strong proficiency in Python and SQL.
• Experience with GitLab and collaborative software development practices.
• Knowledge of machine learning, predictive modelling, NLP and MLOps.
• Experience or interest in generative AI and large language models (LLMs) is an advantage.

Skills and Working Style

• Analytical and results-oriented approach.
• Ability to work independently and propose practical solutions.
• Strong communication skills, including explaining complex technical concepts to non-technical stakeholders.
• Collaborative mindset and willingness to share knowledge.

This role offers the opportunity to work across the full lifecycle of AI and machine learning models, contributing to practical business applications in the insurance sector.