- 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 managersRequirements- 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, ResolumeCore CompetenciesDemonstrates 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 InsightsATS Optimization KeywordsHard Skills- Data Analysis- Statistical Modeling- Machine Learning- Predictive Modeling- Generative Modeling- LLM Fine-Tuning- Prompt Engineering- Embedding Elicitation- A/B Testing- Causal Inference MethodsSoft Skills- Team Leadership- Mentoring- Communication- Collaboration- Problem-SolvingIndustry Keywords- Advanced Analytics- Ethical AI Principles- Data Privacy Laws- GDPR- CCPA- Financial Industry ExperienceTools & Technologies- Pandas- NumPy- Scikit-Learn- PySpark- TensorFlow- PyTorch- HuggingFace Transformers- AWS- Google Cloud- Azure#J-18808-Ljbffr

📌 Data Scientist – Genai, Llms (Madrid)
🏢 Jobtailor
📍 Madrid