Data Scientist (Multiple openings) in Cupertino, CA.

At U.S. Bank, we’re on a journey to do our best. Helping the customers and businesses we serve to make better and smarter financial decisions and enabling the communities we support to grow and succeed.  We believe it takes all of us to bring our shared ambition to life, and each person is unique in their potential. A career with U.S. Bank gives you a wide, ever-growing range of opportunities to discover what makes you thrive at every stage of your career. Try new things, learn new skills and discover what you excel at—all from Day One. Job Description U.S. Bank is seeking a full-time Data Scientist (Multiple openings) in Cupertino, CA.   Essential Responsibilities:   Responsible for developing and implementing data science/machine learning solutions to extract, analyze, and model unstructured data for the AI Center of Excellence (AICoE) at U.S. Bank. The Data Scientist will specialize in developing and programming methods, processes, and systems using advanced statistical, computational, and artificial intelligence (AI) techniques. Specific duties will include:   • Design, implement, and evaluate machine learning and deep learning algorithms, including supervised and unsupervised techniques, such as regression, classification, and clustering; • Apply advanced statistical methods, such as hypothesis testing, regression analysis, and model evaluation metrics to interpret and validate model results; • Develop and implement Transformer-based Natural Language Processing (NLP) models for question answering, entity recognition, relation extraction, summarization from complex documents; • Develop multimodal solutions to extract and analyze both text- and image-based documents and data sources; • Fine-tune and implement Large Language Models (LLMs) and related NLP components using efficient fine-tuning methods, including dataset curation and validation, and prompt optimization techniques; • Build and advance AI systems and agents that enhance automation, ensure regulatory compliance, and strengthen stakeholder trust using retrieval-based reasoning and autonomous decision-making techniques; • Train, fine-tune, and deploy machine learning models across structured and unstructured data modalities, ensuring scalability and reproducibility; • Acquire, clean, and integrate data from multiple sources and build, validate, and optimize predictive and statistical models using advanced machine learning and data visualization techniques; • Design, develop and implement Application Programming Interfaces (APIs) to integrate data pipeline and ML/AI models enabling seamless communication between AI systems and business products; • Identify, analyze, and interpret trends and patterns in complex data to answer business questions and develop actionable recommendations; • Present data and analysis in a clear, concise manner to both technical and non-technical audiences to quickly understand results and recommendations and make data-driven decisions; and • Ensure all data acquisition, sharing, and results of applied recommendations are compliant with company standards. Uses the following tools and technologies: Python (Numpy, Pandas), R, Java, SQL, PyTorch, TensorFlow, Hugging Face Transformers, Linux, SOAP, RESTful APIs and cloud platforms (Azure OpenAI, AWS) for data extraction, data mining, and predictive analytics, Tableau, HTML5, EXCEL VBA scripts, supervised (XGBoost, CatBoost) and unsupervised techniques (Kmodes, K-means). Basic Qualifications:   This position requires a Master’s degree or equivalent in Applied Data Science, Data Science, or Computer Science and 1 year of experience in a data science or related occupation.   Required Skills/Experience: Must also have 12 months of experience with each of the following: 1) Extracting, co