Top Data Science Jobs in Lille

Lead technical sales for enterprise accounts: design and demonstrate Cloudera solutions, discover customer use cases, support pre- and post-sales, partner with account managers, advocate customer needs internally, and evangelize externally.

Senior Product Lead to define, roadmap, and deliver Agentic AI solutions for enterprise programs. Lead requirements gathering, shape end-to-end AI/ML solutions, create PRDs and success metrics, coordinate cross-functional teams, manage stakeholders, and drive adoption, training, and value realization across brands.

The Lead Golang Software Engineer develops server solutions, leads technical designs and code reviews, mentors colleagues, and ensures the quality of engineering practices in the Commercial Systems unit.

Lead GTM strategy and product positioning for key products, create messaging and content, run campaigns and launches, analyze market and competitive trends, and collaborate cross-functionally to drive adoption, pipeline growth, and customer engagement.

Lead end-to-end data efforts: translate business needs into analytics, build forecasting and ML models, create dashboards, automate pipelines, monitor models, and drive data-driven product features.

Lead a team building Owkin's agentic AI Scientist for drug discovery by applying multimodal omics and ML to discover targets, biomarkers, and disease subtypes; collaborate with biologists, engineers, and partners; shape platform capabilities, publish results, and grow a high-performing research team.

As a Data Science Intern, you'll identify frameworks for data-driven business challenges, transform datasets, run analyses, build machine learning models, and communicate results.

The internship involves deploying data processing pipelines, collaborating with clients, conducting R&D in AI and data science, and supporting sales efforts.

Data Scientists at QuantCo will analyze data, build machine learning models, and communicate results to stakeholders, aiming for impactful solutions.

Develop and refine NLP projects by improving LLM models, implementing production models, and conducting performance experiments.