Top Data Science Jobs in Seville

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 and mentor a data science team building ML and LLM solutions for cybersecurity. Translate business needs into research and production ML objectives, prioritize roadmaps, collaborate cross-functionally, and drive technical vision, model development, and operationalization for malware detection and threat analysis.

As the Director of Data Science, you'll mentor teams, oversee projects, drive data-driven decisions, and implement AI and ML solutions while enhancing our data pipeline.

Remote AI/ML Architect to assess current AI/ML landscape, document requirements, and propose SDLC, governance, and deployment approaches. Provide recommendations to architecture and ICT management. Onboarding in the Netherlands (first week). Candidates must be based in Europe with a valid work permit.

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.

The Senior Product Manager will lead the strategic roadmap, conduct market research, manage monetization strategies, and mentor a team while collaborating across various departments.

As a Senior Product Manager, you will define product vision, analyze market trends, manage product KPIs, and collaborate with teams to deliver innovative solutions.

Join Vizzuality's talent pool to contribute to sustainability efforts through science, data, design, and project management roles. Apply with your CV and cover letter to be considered when vacancies arise.

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

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.