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# Data Scientist - Agentic AI

- **Company:** Kyndryl
- **Location:** Madrid, Spain (Remote available)
- **Salary:** €66,864.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Artificial Neural Networks, Computer Engineering, Data Cleansing, Extract Transform Load (ETL), Data Visualization, Python (Programming Language), Machine Learning, NumPy, Tensorflow, Pytorch, Large Language Models, Deep Learning, Generative AI, Pandas, Matplotlib, Core Data, Scikit Learn, Data Analytics, Xgboost, Virtual Agents, Data Pipelines
- **Published:** August 26, 2026
- **Apply:** https://dejobs.org/x/x/97087B1D3F2A453280CCBC0256E85464/job/

## About the Role

* At least 2 years of experience in data science, advanced analytics, or machine learning projects.
 * Solid skills in Python and some of 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.
 * Genuine curiosity and motivation to learn, experiment, and grow in applied AI.
 * Spanish native or high level and fluid English.

Education & Certifications:

Bachelor's degree in Computer engineering, Mathematics, Statistics, Physics, Data Science, or related field.

Preferred Skills:

 * Exposure to data pipelines, ETL processes, and data preparation workflows.
 * Experience with data visualization and presentation of insights to cross-functional teams.
 * Postgraduate or Master's degree in Artificial Intelligence, Machine Learning, or Data Analytics is valued.

## Description

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.
 * Document solutions, experiments, and learnings to support adoption and scalability.
 * Work in a cross-functional, evolving environment , interacting with teams at different levels of AI maturity.


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