Lead Gen AI Data Scientist

Bluevine is the largest small business banking platform in the U.S., redefining how entrepreneurs manage their money. We create modern financial solutions, from checking and lending to payments and beyond, designed to help small business owners grow, thrive, and take control of their financial future. Our best-in-class technology, advanced security, and deep understanding of the small business community give our customers the confidence to focus on what they do best.

Since 2013, we’ve supported more than 750,000 small businesses nationwide. Backed by leading investors like Lightspeed Venture Partners, Menlo Ventures, 83North, and Citi Ventures, our 500+ person global team shares one mission: to give small businesses the financial tools they need to succeed.

We’re innovators driven by big ideas, collaboration, and real impact. Here, you’ll have the freedom to take ownership, grow your career, and make a difference for small business owners across America. Ready to shape what’s next?

At Bluevine, we are building the next generation of AI-powered capabilities that support data-driven decision-making across the company. We are looking for a LeadData Scientist with hands-on experience in Generative AI, Large Language Models, and applied machine learning.

• →Research and evaluate LLMs and Generative AI techniques for business and data science use cases.
• →Collaborate with technical and cross-functional teams to integrate AI capabilities into existing products and workflows.
• →Share knowledge and support the adoption of Generative AI across the organization.
• →Design experiments to adapt and evaluate foundation models using internal and domain-specific data.
• →Build and productionize LLM-based applications, AI agents, and RAG solutions.
• →Develop prompting, retrieval, and evaluation strategies to improve model quality, reliability, and business impact.
• →Work with embeddings, vector databases, and LLM orchestration frameworks.
• →Apply Generative AI to use cases such as risk modeling, fraud detection, and customer analytics.
• →Monitor and improve the performance, cost, and reliability of AI solutions in production.

• 8+ years of hands-on experience in Data Science, Machine Learning & Applied AI. Strong experience with Generative AI and Large Language Models.
• Experience building LLM-based applications, AI agents, RAG solutions, or other production-oriented AI systems.
• Experience with context engineering, model evaluation, fine-tuning, embeddings, or vector databases.
• Strong proficiency in Python and common data science and machine learning tools.
• Experience deploying and monitoring AI or machine learning solutions in production.
• Strong analytical, problem-solving, communication, and collaboration skills.
• Ability to work independently and translate AI capabilities into practical business solutions.

Nice to Have

• Experience with LLMOps, model observability, or cloud-based AI services.
• Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.
• Background in financial services, risk, fraud, or customer analytics.