SENIOR DATA SCIENTIST – CUSTOMERS ANALYTICS

Description

Job Summary: The Senior Data & AI Scientist drives the development of analytical and machine learning models, leading advanced exploratory analysis and basic model industrialization, ensuring solutions aligned with business needs. Key Highlights: 1. Lead advanced exploratory analysis and experimentation 2. Serve as the technical reference in the team for traceability and reproducibility 3. Drive the development of analytical and machine learning models **SENIOR DATA SCIENTIST – CUSTOMERS ANALYTICS. M.ESPAÑA 10/03/26** =============================================================== Location: Majadahonda Recruiter: Estíbaliz López Publication Deadline: 26/03/26 **MISSION** The Senior Data \& AI Scientist is responsible for autonomously driving the development of analytical and machine learning models, leading advanced exploratory analysis, experimentation, and basic model industrialization. This role is critical to ensuring that analytical solutions are built on high-quality data, using robust methods, and remain consistently aligned with business context and requirements—thereby enabling models to deliver real, measurable impact. The role acts as the technical reference within the team, ensuring traceability, reproducibility, and proper integration of models with engineering and business throughout the analytical lifecycle in the Customers domain. Finally, it provides support to ensure the correct execution of AI initiatives within the Customers area—including gathering 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/repositories. Support data \& AI project management (understanding business needs, defining scope, and coordinating multidisciplinary teams—including engineers, architects, business stakeholders, etc.). Propose solutions to business problems in the Customers domain using AI techniques. **REQUIREMENTS** University degree in Engineering, Mathematics, Information Systems, or related field. Business or management education is desirable. Descriptive statistics and probability. Proficiency in statistical ML techniques applied to business (e.g., 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 the data and analytical model lifecycle. Familiarity with neural networks (Keras/TensorFlow is desirable). Machine Learning – Stanford / DeepLearning.AI Generative AI for Everyone – DeepLearning.AI Ability to assess the feasibility of AI initiatives. Ability to propose business solutions using AI techniques. Knowledge of the insurance business and its core processes. Understanding of the Customers domain and its key 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—and highly valued if combined with knowledge of Customers areas or prior work with/for stakeholders in this profile.