Vice President - Data Scientist Lead (LLM/GenAI)

Experteer Overview In this role, you lead AI-driven data initiatives within Commercial Banking to improve planning, efficiency, service, and controls. You will design and deploy generative AI and large language model solutions, collaborating with engineering and product teams to deliver scalable, governed capabilities on Bedrock and Cortex. You’ll build robust evaluation and safety frameworks, mentor junior scientists, and translate business needs into measurable AI outcomes. This position offers high-impact work across content extraction, semantic search, QA, and decision support in a fast-paced environment. Compensation / Benefits * Develop and deliver generative AI and LLM solutions for content extraction, semantic search, QA, summarization, reasoning, and recommendations * Design and manage prompt-based and retrieval-augmented generation systems with orchestration and agentic workflows * Build evaluation frameworks for accuracy, robustness, latency, and cost, including safety checks * Prototype and productionize LLM apps using Amazon Bedrock (model selection, prompts, routing, deployment) * Hands-on work with Cortex (Cortex Analyst) to enable governed analytics and AI-assisted workflows * Apply experience with Bedrock, SageMaker, or Databricks in production settings * Collaborate with engineering to deliver scalable services and robust pipelines * Build data pipelines for structured and unstructured data to support LLM apps * Conduct applied research on prompting, fine-tuning, evaluation, and agent design * Communicate business needs as measurable problem statements and success metrics * Mentor junior data scientists, influence standards, and promote responsible AI practices Tasks * Advanced degree in Data Science, Computer Science, ML, Statistics, or related field, or equivalent practical experience * 5+ years of applied ML/NLP experience with production deployment * Experience with NLP, LLMs, prompt engineering, retrieval-augmented generation, and evaluation methods * Hands-on experience with Amazon Bedrock or equivalent managed LLM platform * Experience with Cortex (Cortex Analyst or related workflows) in an enterprise setting * Strong Python and ML framework skills (PyTorch or TensorFlow), plus pandas, NumPy, scikit-learn * Experience building APIs and integrating LLM/NLP solutions into applications * Experience building data pipelines for structured and unstructured data, embeddings, vector search, indexing, retrieval * Software engineering practices (Git, testing, CI/CD) * Strong communication and stakeholder management; finance knowledge helpful Key requirements * base salary * incentive compensation * comprehensive health care * retirement savings plan * backup childcare * tuition reimbursement

• Prototype and productionize LLM apps using Amazon Bedrock (model selection, prompts, routing, deployment) * Hands-on work with Cortex (Cortex Analyst) to enable governed analytics and AI-assisted workflows * Apply experience with Bedrock, SageMaker, or Databricks in production settings * Collaborate with engineering to deliver scalable services and robust pipelines * Build data pipelines for structured and unstructured data to support LLM apps * Conduct applied research on prompting, fine-tuning, evaluation, and agent design * Communicate business needs as measurable problem statements and success metrics * Mentor junior data scientists, influence standards, and promote responsible AI practices Tasks * Advanced degree in Data Science, Computer Science, ML, Statistics, or related field, or equivalent practical experience * 5+ years of applied ML/NLP experience with production deployment * Experience with NLP, LLMs, prompt engineering, retrieval-augmented generation, and evaluation aaaaa
• • Hands-on experience with Amazon Bedrock or equivalent managed LLM platform * Experience with Cortex (Cortex Analyst or related workflows) in an enterprise setting * Strong Python and ML framework skills (PyTorch or TensorFlow), plus pandas, NumPy, scikit-learn * Experience building APIs and integrating LLM/NLP solutions into applications * Experience building data pipelines for structured and unstructured data, embeddings, vector search, indexing, retrieval * Software engineering practices (Git, testing, CI/CD) * Strong communication and stakeholder management; finance knowledge helpful Key requirements * base salary * incentive compensation * comprehensive health care * retirement savings plan * backup childcare * tuition reimbursement