Top Data Science Jobs in Spain

Lead a cross-functional squad of software engineers and data scientists responsible for a production budgeting platform. Own end-to-end budget allocation, payback-based modeling, technical strategy, reliability, data quality, and product delivery. Develop people, hire talent, make architecture and prioritization trade-offs, and partner with marketing, finance, analytics, and product stakeholders. Translate uncertain modeling outputs into clear business recommendations while building scalable, tested, monitored, and reproducible decision products.

Lead independent product analytics investigations across acquisition, activation, usage, customer experience, and the broader customer journey. Apply statistical analysis, causal inference, experimentation, and data science modeling to uncover product issues, opportunities, churn drivers, and growth insights. Analyze structured, unstructured, and AI-specific data; size opportunities; measure engineering productivity; and translate findings into actionable recommendations for Product, Engineering, Growth, commercial teams, and executives.

Leads forecasting and commercial assessment for Sanofi’s pipeline and external pharmaceutical assets. Responsibilities include patient-based revenue modeling, scenario analysis, market research, competitive assessment, pricing and market-access evaluation, portfolio strategy, and executive presentations. The role partners with commercial, finance, business development, and analytics stakeholders to guide pipeline decisions and assess asset value.

Two-year technology leadership program for recent graduates, offering assignments in AI, intelligent automation, full-stack engineering, data science, decision science, data insights, and cybersecurity. Participants receive training, mentoring, certifications, and hands-on project leadership opportunities while developing technical, business, and leadership skills across Johnson & Johnson’s European operations.

Own Fever’s pricing product vision and roadmap across live entertainment sectors. Define pricing structures, optimization levers, algorithms, experimentation standards, and sector-specific solutions. Partner with data science, engineering, commercial, legal, and marketing teams to evaluate demand, elasticity, pricing fairness, and business outcomes. Serve as the organization’s pricing authority while guiding the development of scalable models, experiments, and optimization capabilities.

Develop GreyNoise’s cybersecurity channel business across Europe by recruiting and activating partners, building joint business plans, enabling partner teams, generating qualified pipeline, and co-selling enterprise and government opportunities. The role manages partner relationships, channel strategy, revenue targets, forecasting, commercial negotiations, partner reviews, technical enablement, demand generation, and cybersecurity event representation.

Own the Mapping & Content product domain end to end, including strategy, prioritization, economics, and outcomes. Lead efforts to match hotel rooms and content across suppliers, languages, and formats with high accuracy and coverage. Partner closely with engineering and data science teams on entity resolution, search, matching, catalog, identity, recommendation, and content-quality problems. Identify high-value failures, make trade-offs between precision and coverage, and help build Nuitee’s product organization in a fast-moving environment.

Develop and evaluate AI, generative AI, LLM, RAG, and agentic workflow solutions for pharmaceutical development, manufacturing, regulatory, quality, and supply-chain processes. Build reusable components, apply responsible AI and software engineering practices, validate outputs, and collaborate with scientific and technical stakeholders in regulated environments. The role requires Python development, pharmaceutical CMC knowledge, and communication with technical and non-technical teams.

Develop and validate applied AI, machine learning, and statistical models supporting pharmaceutical development, manufacturing, clinical supply, quality, regulatory, and CMC activities. Responsibilities include exploratory data analysis, feature engineering, model tuning, software development, testing, documentation, reproducibility, and cross-functional collaboration with scientific and technical teams.

Summer intern supporting computer vision and multimodal AI research for medical imaging and video. Responsibilities include interviewing clinical stakeholders, identifying business value, developing and evaluating computer vision models, extracting insights from reports, and communicating technical findings. Work covers modalities including endoscopy, ultrasound, X-rays, dermatology images, retinal OCT, and histopathology.

Oversee end-to-end clinical data science programs, including planning, resource allocation, budgets, timelines, risk management, and delivery milestones. Coordinate data scientists, statisticians, clinical researchers, clients, and cross-functional teams. Provide guidance on clinical data management, systems, methodologies, regulations, and data risk. Manage escalations, financial performance, reporting, proposals, and client partnerships while mentoring teams and supporting strategic clinical data science plans.

Partner with senior leaders to develop Data Science and AI talent strategies. Lead market mapping, strategic sourcing, passive candidate engagement, stakeholder management, and end-to-end recruitment while providing talent-market insights and an exceptional candidate experience.

Data Science Intern supporting Finance EMEA by developing and assessing forecasting models, exploring datasets, improving data quality and governance, documenting findings, and experimenting with Generative AI and agentic technologies. The role requires Python knowledge, analytical ability, collaboration, autonomy, and interest in applying data science to financial performance within the medical device industry.

Advise clients on becoming data-driven by assessing data and ML maturity, identifying use cases, and defining implementation roadmaps. Collaborate with data scientists, engineers, and architects on AI solutions, governance, MLOps, and analytics centers of excellence. Support business development, client relationships, conferences, sales meetings, thought leadership, and the growth of the Data & AI consulting practice.

Advise C-level life sciences and healthcare executives on AI and data strategies, lead large-scale digital transformations, develop client solutions, and guide implementation and scaling. Build new business opportunities, manage long-term client relationships and multimillion-dollar portfolios, lead cross-functional engagement teams, and ensure high-quality analytical deliverables. Contribute to practice development and organizational growth.

As a Fraud Data Analyst, you will architect real-time defense strategies against payment fraud, develop precision rules, optimize decisioning stacks, and report performance metrics to senior leadership while ensuring a frictionless user experience.

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.

Work with clients to design and deliver software and technical solutions across fullstack, backend, data, cloud, AI, and DevOps. Collaborate in teams, shape products, and drive implementations while growing professionally with mentorship and coaching.

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 an AI Product Manager, you will lead the AI product development lifecycle, collaborate with teams, and align AI technologies with user needs.

Data Science Intern supporting mobility demand forecasting, fleet optimization, user feedback analysis, and other machine learning use cases. Responsibilities include exploring datasets, developing and evaluating models, feature engineering, deploying proofs of concept, monitoring production models, and communicating findings. The role requires Python, data science libraries, SQL, statistics, machine learning fundamentals, Git, and professional communication in Spanish, French, and English.

Lead and develop a team of Data Scientists and ML Engineers building production machine-learning systems for logistics. Drive AI adoption, roadmap prioritization, agile execution, and measurable business outcomes. Partner with Product Managers, Staff ML Engineers, and the MLOps platform team to deploy scalable solutions. The role requires deep hands-on experience with production ML, recommender systems, pricing algorithms, statistical models, and modern data and AI technologies, alongside strong people leadership and executive communication skills.

Seeking an independent board director with expertise in ML-driven products and data platforms. The role focuses on guiding the company's data-driven culture and product strategies, not on day-to-day operations.

Lead the technical and product vision for the UA DSP, unifying Data Science, Data Engineering, Analytics, BI, and bidding/prediction backend. Own roadmap from bidding/prediction to reporting, manage and grow a ~20-person cross-functional team, partner with GTM and sales, and drive transition from managed-service to self-service advertiser tooling.

The internship involves setting up data processing pipelines, collaborating with clients, conducting R&D, supporting sales, and understanding product lifecycles in AI for insurance.