Data Scientist

Data Scientist – LLM Expert – Kyndryl Location: Madrid, Community of Madrid, Spain About Kyndryl At Kyndryl, we design, build, manage and modernize the mission‐critical technology systems that the world depends on every day. We are always moving forward – always pushing ourselves to go further in our efforts to build a more equitable, inclusive world for our employees, our customers and our communities. The Role We're looking for exceptional talent to join our AI Agentic Innovation Hub at Kyndryl The AI Agentic Innovation Hub stands as Kyndryl's center of excellence for advanced and agentic artificial intelligence. Our mission is to lead the design and deployment of transformative AI solutions that bridge frontier research with real‐world impact — scalable, secure, and driven by measurable value. Job Description As an Associate Data Scientist at Kyndryl's AI Innovation Hub, you'll be part of a team that turns data into intelligent, high‐impact solutions. You'll collaborate with senior data scientists, ML engineers, and AI architects to design, train, and validate predictive and machine learning models that tackle real business and operational challenges. You'll participate in every stage of the model lifecycle — from data exploration and feature engineering to modeling, evaluation, and documentation — helping transform raw data into actionable insights. This is a hands‐on, learning‐focused role in which you'll work with modern technologies, contribute to scalable AI solutions, and grow your expertise within an environment that values experimentation, rigor, and curiosity. If you're passionate about data, eager to learn from experienced professionals, and ready to contribute to cutting‐edge AI initiatives for leading global clients, this is your opportunity to build the foundation of your career in applied data science. Your Mission Collaborate with senior scientists and engineers to develop and validate machine learning and predictive models. Participate in the end‐to‐end model lifecycle— from data collection and preparation to training, evaluation, and documentation. Contribute to feature engineering, exploratory analysis, and performance optimization of models. Apply statistical and analytical techniques to extract meaningful patterns and insights from data. Assist in model deployment and monitoring within MLOps environments and cloud platforms. Document experiments and ensure transparency, reproducibility, and traceability of results. Stay up to date with new algorithms, frameworks, and best practices in data science and applied AI. Actively contribute to a collaborative, knowledge‐sharing culture within the Hub. Essential Qualifications 2–4 years of experience in data science, advanced analytics, or machine learning projects. Practical experience building and validating models for classification, regression, or segmentation tasks. Solid skills in Python and core data science libraries (Pandas, NumPy, Scikit‐learn, Matplotlib, XGBoost, LightGBM). Familiarity with neural networks and deep learning frameworks (TensorFlow, PyTorch). Strong understanding of data preprocessing, handling missing values, unbalanced datasets, and outlier detection. Experience with model evaluation and validation (ROC, AUC, F1, RMSE, precision, recall, cross‐validation). Basic knowledge of cloud AI platforms (Azure ML, Vertex AI, SageMaker, Databricks). Awareness of model versioning and experiment tracking tools (MLflow, DVC). Understanding of Responsible AI concepts — bias mitigation, transparency, and interpretability. Education & Certifications Bachelor's degree in Computer Engineering, Mathematics, Statistics, Physics, Data Science, or related field. Postgraduate or Master's degree in Artificial Intelligence, Machine Learning, or Data Analytics is valued. Complementary training or certifications in Machine Learning, Data Science, or MLOps are a plus. Demonstrated interest in continuous learning and professional growth in applied AI. Preferred Skills Exposure to data pipelines, ETL processes, and data preparation workflows. Familiarity with SQL/NoSQL databases and working with APIs for data access. Experience supporting model integration and testing within production environments. Curiosity for new algorithms, frameworks, and emerging tools in AI and MLOps. Experience with data visualization and presentation of insights to cross‐functional teams. Ability to collaborate effectively in agile, fast‐paced environments. Soft Skills Analytical curiosity and a scientific mindset, eager to understand problems deeply and find evidence‐based solutions. Clear and structured communication, both in technical documentation and team collaboration. Logical and organized thinking, applying rigorous methodologies to problem‐solving. Collaborative spirit, working proactively with technical and business profiles to deliver results. Attention to detail and quality, ensuring reproducibility and reliability in models and analyses. Continuous learning attitude, exploring new techniques, algorithms, and tools to strengthen the Hub's capabilities. Adaptability and growth orientation, thriving in a dynamic, innovation‐driven environment. What You Can Expect With state‐of‐the‐art resources and Fortune 100 clients, every day is an opportunity to innovate, build new capabilities, new relationships, new processes, and new value. Kyndryl cares about your well‐being and prides itself on offering benefits that give you choice, reflect the diversity of our employees, and support you and your family through the moments that matter – wherever you are in your life journey. Our employee learning programs give you access to the best learning in the industry to receive certifications, including Microsoft, Google, Amazon, Skillsoft, and many more. Through our company‐wide volunteering and giving platform, you can donate, start fundraisers, volunteer, and search over 2 million non‐profit organizations. At Kyndryl, we invest heavily in you, we want you to succeed so that together, we will all succeed. Get Referred If you know someone that works at Kyndryl, when asked 'How Did You Hear About Us' during the application process, select 'Employee Referral' and enter your contact's Kyndryl email address. #J-18808-Ljbffr