VP Data Scientist Lead (GenAI)

Salary: $61,000 - 101,000 per year Requirements:

• We require an advanced degree in Data Science, Computer Science, Machine Learning, Statistics, or a related quantitative discipline, or equivalent hands-on experience.
• We need 5+ years of applied experience developing machine learning or natural language processing solutions, including production deployment in a fast-paced setting.
• We expect experience with natural language processing and large language models, including prompt engineering, retrieval-augmented generation, and evaluation methods.
• We require practical experience with Amazon Bedrock or a comparable managed large language model platform for building and deploying generative artificial intelligence solutions.
• We look for experience with Cortex, including Cortex Analyst or similar enterprise workflows.
• We require strong Python skills and familiarity with machine learning or deep learning frameworks such as PyTorch or TensorFlow, along with tools such as pandas, NumPy, and scikit-learn.
• We expect experience building APIs and integrating large language model or natural language processing solutions into applications and services.
• We require experience creating data pipelines for structured and unstructured data, with knowledge of embeddings, vector search, indexing, and retrieval patterns.
• We look for familiarity with software engineering practices, including Git or version control, code quality, testing, and CI/CD fundamentals.
• We need strong communication and stakeholder management skills, with the ability to present trade-offs, risks, and outcomes clearly.
• We value strong analytical ability and working knowledge of financial services, markets, or asset management concepts.
• Preferred: deep understanding of large language model techniques, including agents, planning, reasoning, and related methods.
• Preferred: experience with machine learning operations, including experiment tracking, model registry, monitoring, drift and performance tracking, incident management, and rollback.
• Preferred: experience with cloud deployment patterns, ideally on Amazon Web Services, and production runtime environments such as containers or orchestration platforms.

• We develop and deliver generative artificial intelligence and large language model solutions for content extraction, semantic search, question answering, summarization, reasoning, and recommendation use cases.
• We design, deploy, and manage prompt-based and retrieval-augmented generation systems, including orchestration patterns and agentic workflows such as tool use, structured outputs, and multi-step reasoning.
• We build evaluation and testing frameworks to measure accuracy, faithfulness, robustness, latency, and cost, including red-teaming and safety checks where appropriate.
• We leverage Amazon Bedrock to prototype and productionize large language model applications, including model selection, prompt templates, routing, and deployment patterns.
• We work hands-on with Cortex, including Cortex Analyst, to enable governed analytics experiences and generative artificial intelligence-assisted workflows.
• We apply hands-on experience in environments such as Amazon Bedrock, Amazon SageMaker, or Databricks.
• We collaborate with engineering teams to deliver scalable services, including APIs, batch jobs, and pipelines, while maintaining strong software engineering discipline and operational readiness.
• We build and maintain data pipelines for structured and unstructured data to support retrieval, indexing, and preprocessing for large language model applications.
• We conduct applied research by reviewing scientific articles and current techniques in prompting, fine-tuning, evaluation, and agent design, then translate them into practical improvements.
• We communicate clearly with technical and non-technical stakeholders by turning business needs into measurable problem statements, solution designs, and success metrics.
• We mentor junior data scientists, influence standards, and drive adoption of responsible artificial intelligence practices.

• CI/CD
• Cloud
• Databricks
• Fine-tuning
• Git
• Incident Management
• Support
• Machine Learning
• PyTorch
• Python
• TensorFlow
• Web
• numpy
• pandas

More:

We are partnering with hackajob to connect with exceptional professionals for this role on behalf of J.P. Morgan. You would join our Global Services Insights & Analytics team as a Vice President, Data Scientist Lead, helping transform data into actionable insights and improving planning, efficiency, service, and controls within Commercial Banking. We offer the opportunity to lead high-impact generative artificial intelligence solutions across financial services use cases, with a focus on reliable, scalable, and governed capabilities. Our total rewards package includes competitive base salary, and eligible roles may also receive commission-based pay and/or discretionary incentive compensation. We provide a range of benefits and programs, including comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching, and more, with additional compensation and benefits details shared during the hiring process. We are committed to diversity, inclusion, and reasonable accommodations. Our Commercial & Investment Bank is a global leader across banking, markets, securities services, and payments, serving clients in more than 100 countries.

last updated 40 week of 2026