This job is with Kyndryl, an inclusive employer and a member of myGwork – the largest general platform for the LGBTQ+ business community. At Kyndryl, we run and reimagine the mission-critical technology systems that drive advantage for the world's leading businesses. with proven expertise and a continuous flow of AI-powered insight, enabling smarter decisions, faster innovation, and a lasting competitive edge. As a Senior Data Scientist at Kyndryl , you will play a key role in designing, developing, and deploying advanced Artificial Intelligence solutions that address complex business challenges and deliver measurable value to our clients. You will work across the evolving AI landscape, combining traditional Machine Learning and advanced analytics with Generative AI, Large Language Models (LLMs), and emerging Agentic AI technologies to build intelligent, scalable, and reliable solutions. As part of a multidisciplinary team of AI specialists, data scientists, engineers, and architects, you will contribute to the full AI lifecycle, from problem definition and experimentation to production deployment, monitoring, and continuous improvement. Translate complex business needs into actionable AI and Data Science solutions, identifying opportunities where Machine Learning, Generative AI, and Agentic AI can create tangible value. Explore and evaluate emerging AI methodologies, architectures, and technologies, combining established Data Science approaches with the latest advances in foundation models and intelligent agents. Build Machine Learning solutions: Design, develop, train, and evaluate predictive and analytical models using statistical methods, supervised and unsupervised learning, deep learning, and other advanced Data Science techniques. Explore and implement Agentic AI:



Develop intelligent agents and multi-agent systems capable of reasoning, planning, interacting with tools and enterprise systems, and executing complex workflows with appropriate human oversight. Define and implement evaluation methodologies to assess model accuracy, reliability, robustness, and business performance, including specific approaches for evaluating LLM-based and agentic systems. Lead the technical development of AI solutions, from exploratory analysis, prototyping, and experimentation to deployment and integration into enterprise environments. Collaborate with engineering and platform teams to establish reproducible, maintainable, and scalable AI solutions, incorporating versioning, automated testing, monitoring, and continuous improvement. Contribute to the evaluation, observability, and continuous improvement of agentic AI systems, monitoring agent behavior, tool interactions, reliability, and end-to-end process performance, while supporting responsible autonomy and human oversight. Leverage Python, leading Machine Learning and Deep Learning frameworks, cloud AI platforms, and emerging GenAI and agentic frameworks, selecting the most appropriate technologies for each use case. Work alongside AI architects, software engineers, data engineers, domain experts, and business stakeholders to design integrated, production-ready AI solutions. Contribute to architectural and technical decisions,



promote engineering best practices, and support the development of junior Data Scientists and AI practitioners. Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Mathematics, Statistics, Engineering, or a related technical field, combined with solid professional experience in Data Science, Machine Learning, or AI development. Strong Data Science and Machine Learning foundations: Proven experience designing, developing, and evaluating Machine Learning models, with a solid understanding of statistical methods, supervised and unsupervised learning, and Deep Learning techniques. Strong proficiency in Python and relevant Data Science and AI libraries, such as Scikit-learn, PyTorch, TensorFlow, Hugging Face, or equivalent technologies. Experience across the AI development lifecycle, including data preparation, experimentation, model evaluation, deployment, and monitoring, with familiarity with MLOps, LLMOps, and emerging AgentOps practices. Cloud AI platforms: Experience with Azure AI, AWS, or Google Cloud AI/ML services. Enterprise AI projects: Previous involvement in AI-driven digital transformation initiatives, enterprise automation, or the development of AI-powered business solutions. A Master's degree, PhD, scientific publications, open-source contributions, or active participation in technical and research communities will be considered an advantage. Your career with us isn't just a job-it's an adventure with purpose.

We offer
a dynamic, hybrid-friendly culture that supports your well-being and empowers you to grow. Our Be Well programs are thoughtfully designed to support your financial, mental, physical, and social health-because we know that when you feel your best,

📌 Data scientist Junior (Madrid)
🏢 Kyndryl
📍 Madrid