- 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