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

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