Top Data Science Jobs in Spain

Leads the vision, strategy, and execution of AI-powered data and analytics capabilities for Medical Affairs. Oversees patient journey analytics, advanced segmentation, stakeholder evaluation, data architecture, governance, and AI automation frameworks. Evaluates external innovations, builds proprietary solutions, manages analytics delivery teams, and advises senior leadership on data investments, innovation roadmaps, compliance, ethics, and competitive advantage.

Design, deliver, and continuously improve scalable production AI solutions using LLMs, RAG, agentic AI, machine learning, and document intelligence. Build cloud-native systems on Azure using software engineering, architecture, DevOps, and MLOps practices. Own AI platforms and models across deployment, monitoring, security, governance, and optimization. Lead technical initiatives, collaborate with product and business teams, mentor engineers, and translate business needs into measurable outcomes.

Lead and mentor a data science team developing machine learning systems for threat detection and agentic AI. Set ML technical strategy, standards, roadmaps, and deployment practices; guide projects from research through production; collaborate with security, engineering, and product teams; develop advanced malware and behavioral threat models; communicate insights; and contribute to research, publications, patents, and hands-on technical work.

Lead end-to-end ML product roadmaps and initiatives (e.g., Attachment Matcher, Transaction Categorizer). Collaborate with data scientists, engineers, and stakeholders to define, deliver, and monitor ML solutions that drive measurable business value for SMEs across Qonto's platform.

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.

Leads AI literacy and adoption initiatives across R&D, providing clinical and scientific expertise. Partners with stakeholders and subject matter experts to develop accurate, practical AI education, use cases, communications, toolkits, and enablement resources. Translates AI concepts into relevant applications for scientific and clinical audiences, evaluates AI tools and limitations, and supports responsible adoption, cross-functional collaboration, and organizational transformation.

Own IT solutions and service coordination for pharmaceutical R&D Data Science teams. Translate scientific requirements into scalable applications, platforms, pipelines, and cloud architectures while coordinating infrastructure, security, data, AI, vendors, and support teams. Manage solution lifecycles from ideation through production, ensure GxP, security, compliance, and data integrity standards, prioritize demand, track KPIs, and enable bioinformatics, omics, modeling, advanced analytics, and AI/ML initiatives.

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.

Lead discovery, design and delivery of Big Data and AI products for internal Kyivstar teams. Engage stakeholders, define vision, prioritize roadmaps, manage PoCs/MVPs to production, coordinate data and engineering teams, run pilots and measure business impact to ensure solutions create measurable value.

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.

Own data science projects from business questions through customer-facing AI products. Build, evaluate, deploy, and maintain machine learning models; advise internal teams; research advanced AI applications; support important data domains; and collaborate with stakeholders to assess production readiness. The role requires Python-based machine learning development, cloud orchestration, generative AI experience, production deployment experience, and strong communication skills.

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

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.

Fully funded three-year postdoctoral fellowship focused on developing and improving scientific services for research infrastructures. Fellows conduct technology-development projects aligned with EMBL research areas, receive training in infrastructure operations and management, and build professional networks through secondments and job shadowing. Projects may involve computational science, imaging, optical engineering, robotics, mechanics, biotechnology, or omics. Applicants must hold or have defended a Ph.D. by September 30, 2026, possess relevant STEM training and technology-development experience, and demonstrate strong research potential.

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.

Develop statistical and machine learning solutions for customer and energy-transition challenges, from problem discovery and experimentation through prototype validation and production handover. Lead end-to-end analytical workstreams, collaborate with customers, engineers, domain experts, and product teams, and mentor data scientists. Build models for time-series and text data using Python and data science libraries, working with databases, APIs, pipelines, Kubernetes, Linux, Git, and Docker.

Leads clinical data science delivery and team development, designing advanced statistical models and machine learning methods for clinical research. Oversees data analysis, management, regulatory compliance, and trial optimization while collaborating with clinical, biostatistical, and regulatory teams. Communicates complex insights to senior stakeholders and external partners and drives innovation across clinical development programs.

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.

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