Data Scientist - English

Partially Remote Full time 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.You will join Kyndryl’s transversal initiative on Agentic and Generative AI , contributing to the design, implementation, and evolution of data-and model-driven solutions that support both client delivery and internal operational efficiency.Collaborate with data scientists, engineers, and architects to build applied AI and agent-based solutions .Develop, validate, and evolve machine learning models and LLM-based components for real business and delivery use cases.Participate across the solution lifecycle: data exploration, prototyping, validation, and continuous improvement.Contribute to the development of agents, analytical pipelines, and decision logic , balancing technical quality with practical delivery needs.Solid skills inPythonand some of core data science libraries (Pandas, NumPy, Scikit-learn, Matplotlib, XGBoost, LightGBM).Familiarity withneural networksand deep learning frameworks (TensorFlow, PyTorch).Spanish native or high level and fluid English.Bachelor’s degree inComputer engineering,Mathematics,Statistics,Physics,Data Science, or related field.Exposure todata pipelines,ETL processes, anddata preparation workflows.Postgraduate or Master’s degree inArtificial Intelligence,Machine Learning, orData Analyticsis valued.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.You won’t just contribute - you’ll make a difference, tackling meaningful projects that sharpen your skills and fuel your growth.You’ll develop in-demand skills to grow your career and achieve your ambitions with access to cutting-edge learning opportunities - from certifications with Microsoft, Google, and Amazon to coaching and hands-on experiences.And through it all, you’ll be part of a culture that values empathy, restless learning, and a #

Familiarity withneural networksand deep learning frameworks (TensorFlow, PyTorch). Spanish native or high level and fluid English. Bachelor’s degree inComputer engineering,Mathematics,Statistics,Physics,Data Science, or related field. Exposure todata pipelines,ETL processes, anddata preparation workflows. Postgraduate or Master’s degree inArtificial Intelligence,Machine Learning, orData Analyticsis valued. 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. You won’t just contribute - you’ll make a difference, tackling meaningful projects that sharpen your skills and fuel your growth. You’ll develop in-demand skills to grow your career and achieve your ambitions with access to cutting-edge learning opportunities - from certifications with Microsoft, Google, and Amazon to coaching and hands-on experiences. And through it all, you’ll be part of a culture that values empathy, restless learning, and a #

Partially Remote Full time 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. You will join Kyndryl’s transversal initiative on Agentic and Generative AI , contributing to the design, implementation, and evolution of data-and model-driven solutions that support both client delivery and internal operational efficiency. Collaborate with data scientists, engineers, and architects to build applied AI and agent-based solutions . Develop, validate, and evolve machine learning models and LLM-based components for real business and delivery use cases. Participate across the solution lifecycle: data exploration, prototyping, validation, and continuous improvement. Contribute to the development of agents, analytical pipelines, and decision logic , balancing technical quality with practical delivery needs.