Job Summary: The Senior Data & AI Scientist drives the development of analytical and machine learning models, leading advanced analysis, experimentation, and industrialization to deliver real and measurable impact in the Customer domain. Key Highlights: 1. Drive the development of analytical and machine learning models. 2. Lead advanced exploratory analysis and experimentation. 3. Serve as the technical reference in the Customer domain. **SENIOR DATA SCIENTIST – CUSTOMER ANALYTICS. M. SPAIN 10/03/26** =============================================================== Location: Majadahonda Recruiter: Estíbaliz López Publication Deadline: 26/03/26 **MISSION** The Senior Data \& AI Scientist’s mission is to autonomously drive the development of analytical and machine learning models, leading advanced exploratory analysis, experimentation, and basic model industrialization. This role is critical to ensuring analytical solutions are built on high-quality data, using robust methods, and always aligned with business context and needs—thereby enabling models to deliver real and measurable impact. Acts as the technical reference within the team, ensuring traceability, reproducibility, and proper integration of the model with engineering and business throughout the analytical lifecycle in the Customer domain. Finally, provides support to ensure correct execution of AI initiatives within the Customer area—capturing and defining business requirements, guaranteeing functional scope, and collaborating on end\-to\-end project delivery. **RESPONSIBILITIES** Design and execute advanced EDA and supervised/unsupervised experimentation; document findings and metrics. Train, evaluate, and refine classical and some advanced models; prepare handover to MLOps/engineering. Collaborate with Engineering and Business/Analysts to integrate the model into the value stream. Ensure data traceability and reproducibility in notebooks/repos. Support data \& AI project management (understanding business needs, defining scope, and coordinating multidisciplinary teams (engineers, architects, business stakeholders, etc.). Propose business problem solutions in the Customer domain using AI techniques. **REQUIREMENTS** University degree in Engineering, Mathematics, Information Systems or related field. Business or management studies preferred. Descriptive statistics and probability. Proficiency in statistical ML techniques applied to business (linear regression, decision trees, k\-NN). Python for data analysis (Pandas, NumPy, Scikit\-learn). Model evaluation techniques (accuracy, precision, recall). Experience working with notebooks (Jupyter or similar environments). Understanding of data and analytical model lifecycles. Basic knowledge of neural networks (Keras/TensorFlow preferred). Machine Learning – Stanford / DeepLearning.AI Generative AI for Everyone – DeepLearning.AI Ability to assess the feasibility of AI initiatives. Propose business solutions using AI techniques. Knowledge of the insurance business and its key processes. Familiarity with the Customer domain and its core functions. Experience in data analysis, modeling, and Data \& AI projects with demonstrated autonomy (3\-5 years). Participation in projects as a seasoned technical professional applying exploratory analysis or supervised machine learning techniques (3\-5 years). Experience working in collaborative environments with technical profiles under supervision (3 years). Experience in insurance companies; knowledge of Customer areas or prior work with/for stakeholders in this profile is highly valued.