Manage and execute key analytical projects within the DATA area, aligning with strategic objectives

Lead analytical teams to ensure successful project delivery

Analyze large and complex datasets to uncover trends and insights that drive business decisions

Develop predictive and generative models using statistical, machine learning, and LLM techniques

Evaluate, fine-tune, and optimize LLM models for domain-specific applications

Integrate LLMs into analytical solutions

Lead iterative development of LLM-based solutions

Construct knowledge bases, datasets, and performance evaluation methodologies

Collaborate with product managers, engineers, and designers to implement data-driven solutions

Integrate LLM capabilities effectively

Present findings and recommendations to stakeholders across the organization

Guide and mentor less experienced team members

Ensure deliverables meet Advanced Analytics governance standards and best practices

Build end-to-end data products incorporating cutting-edge AI for banking processes

Help develop an AI-supported customer relationship model for customers and managers

Requirements

Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field

5+ years of experience working as a Data Scientist, including significant work with LLMs and multidisciplinary projects

Advanced technical knowledge of LLMs, including fine-tuning, prompt engineering, embedding elicitation, and model optimization

Deep expertise in Python, statistical modeling, and machine learning

Strong proficiency in Pandas, NumPy, and scikit-learn

Hands-on experience with PySpark, TensorFlow, PyTorch, and HuggingFace Transformers

Proficiency in the end-to-end lifecycle of ML models, from dataset creation and EDA to testing and monitoring/retraining





In-depth understanding of LLM risks, including hallucination, biases, and unpredictability

Deep knowledge of machine learning techniques applied to complex business problems, including A/B testing for model performance

Excellent ability to translate complex technical concepts into actionable business insights

Knowledge of ethical AI principles and data privacy laws such as GDPR and CCPA

Previous experience in the financial industry is a plus

PhD in Computer Science, Statistics, Mathematics, or a related field is a plus

Experience with AWS, Google Cloud, or Azure, including Docker and Kubernetes is a plus

Knowledge and application of causal inference methods is a plus

Skills: Data Processing, English Language, Resolume

Core Competencies Demonstrates expertise in managing analytical projects and leading teams to deliver data-driven solutions, with a strong focus on LLM development and optimization. Proficient in translating complex data insights into actionable business strategies while adhering to advanced analytics governance standards.

Highest-signal resume keywords

LLM Development and Optimization

Python Programming

Statistical Modeling

Machine Learning Techniques

Data Analysis and Insights

ATS Optimization Keywords Hard Skills

Data Analysis

Statistical Modeling

Machine Learning

Predictive Modeling

Generative Modeling

LLM Fine-Tuning

Prompt Engineering

Embedding Elicitation

A/B Testing

Causal Inference Methods

Soft Skills

Team Leadership

Mentoring

Communication

Collaboration

Problem-Solving

Industry Keywords

Advanced Analytics

Ethical AI Principles

Data Privacy Laws

GDPR

CCPA

Financial Industry Experience

Tools & Technologies

Pandas

NumPy

Scikit-Learn

PySpark

TensorFlow

PyTorch

HuggingFace Transformers

AWS

Google Cloud

Azure

📌 Data Scientist – GenAI, LLMs (Madrid)
🏢 Jobtailor
📍 Madrid