About Lesaffre:Lesaffre, a global leader in fermentation and yeast production, is dedicated to harnessing the power of data to drive innovation and create value across diverse sectors, from baking to biotechnology. Join our Digital, Data, and Tech team to be part of a journey that transforms our business through advanced analytics and AI.

Role Overview:As a Lead Data Scientist at Lesaffre, you’ll play a crucial role in shaping our data science initiatives. Focused on technical and methodological guidance, you will work hands-on to design, build, and deploy artificial intelligence solutions at scale. With strong expertise in cloud-based data science and ML solutions and a forward-looking approach to Generative AI, you’ll be instrumental in advancing our AI capabilities across our four transformation pillars: Customer Centricity, Corporate Functions, Smart Operations, and Augmented R&D.

Key Responsibilities:

• Technical Leadership: Provide advanced technical guidance to our data science projects, ensuring high-quality development and deployment of machine learning models.
• Model Design & Deployment: Lead efforts to design, build, and deploy machine learning solutions at scale on cloud platforms, optimizing for robustness, efficiency, and scalability.
• Methodological Expertise: Develop and advocate best practices in data science methodology, ensuring our approach is rigorous, innovative, and aligned with business goals.
• Generative AI Innovation: Leverage experience with Generative AI to identify, develop, and integrate Gen AI solutions that enhance our AI initiatives.
• Collaboration: Work closely with cross-functional teams, including data engineering, product, governance and business stakeholders, to understand requirements and deliver impactful solutions with an agile mindset.

Education: Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a related field.

Experience: At least 7 years of hands-on experience in data science, with a proven track record of designing, building, and deploying scalable machine learning solutions on cloud platforms. Previous experience in developing data science solutions for industrial applications is highly valued.

Technical Expertise:

• Deep expertise in cloud platforms (Snowflake, AWS, GCP, or Azure), including building and managing data pipelines, deploying models, and implementing robust monitoring frameworks.
• Strong proficiency in Python, SQL, and machine learning libraries such as TensorFlow, PyTorch, and Scikit-Learn.
• Hands-on experience with MLOps practices and CI/CD pipelines for deploying, monitoring, and maintaining machine learning models in production environments.
• Advanced understanding of Generative AI technologies and demonstrated ability to apply them effectively in practical business contexts.

Analytical Skills: Exceptional problem-solving abilities with a focus on delivering impactful, data-driven solutions.

Soft Skills:

• Outstanding communication and presentation skills, with the ability to convey complex technical concepts to diverse audiences.
• A proactive and service-oriented mindset, driving collaboration and results.
• A commitment to continuous learning, staying abreast of emerging tools, methodologies, and trends in AI and data science.
• Strong mentoring capabilities, with the ability to guide and support junior data scientists and foster collaboration around technical and methodological topics.
• Adaptability to work effectively in a dynamic, fast-paced environment with evolving foundations.