Experteer Overview
As a Senior Data Scientist at Kyndryl, you design, develop, and deploy AI solutions that address complex business challenges and deliver measurable value. You work with Generative AI, LLMs, and agentic AI within a multidisciplinary team to drive end-to-end AI lifecycles, from problem framing to production and continuous improvement. You will collaborate with clients to translate needs into impactful AI use cases and scalable, responsible solutions. This role offers exposure to cutting-edge GenAI technologies and enterprise-scale impact, aligned with Kyndryl's mission of powering customer progress.

Compensaciones / Incentivos
• Translate business needs into AI/Data Science solutions to unlock value
• Explore emerging AI methodologies and architectures, combining DS with foundation models and agents
• Collaborate with clients and stakeholders to define AI use cases and communicate findings
• Design and implement Generative AI applications (LLMs, embeddings, RAG, prompts)
• Develop ML models using statistical methods and deep learning
• Create agentic AI systems, including multi-agent workflows with human oversight
• Define evaluation methods for model accuracy, reliability, and business impact
• Lead AI solution development from concept to production and enterprise integration
• Apply MLOps, LLMOps, and AgentOps practices for reproducibility and scalability
• Support responsible AI through governance, explainability,



and security considerations
• Collaborate with AI architects, engineers, and business stakeholders
• Provide technical leadership and mentor junior practitioners
• Stay current with AI research and contribute to internal knowledge sharing
• Engage customers through workshops, demos, and solution design activities

Responsabilidades
• Bachelor's or Master's degree in a relevant technical field with solid professional DS/AI experience
• Strong foundations in Data Science and Machine Learning, including statistics and both supervised and unsupervised methods
• Hands-on Generative AI and LLM experience: prompts, embeddings, and RAG
• Practical knowledge of agentic AI: tool integration, orchestration, reasoning workflows
• Proficiency in Python and DL/ML libraries (Scikit-learn, PyTorch, TensorFlow, Hugging Face)
• Experience across the AI lifecycle: data prep, experimentation, evaluation, deployment, monitoring
• Familiarity with MLOps, LLMOps, and emerging AgentOps practices
• Analytical problem-solving with ability to translate business needs into technical solutions
• Strong collaboration and communication skills with stakeholders

Requisitos principales
• hybrid-friendly culture
• Be Well programs
• continuous learning opportunities
• certifications (Microsoft, Google, Amazon)
• coaching and hands-on experiences
• career development pathways

📌 Data Scientist - Agentic AI (Barcelona)
🏢 Kyndryl
📍 Barcelona