Data Science Manager

Summary

Join Mercury as the Data Science Manager for Product Expansion and lead the development of data infrastructure, AI systems, and analytics capabilities for our next generation of financial products. You will architect comprehensive data solutions, create self-service data products, build ML systems, and develop measurement frameworks. This role involves leading a team of senior data scientists, partnering with cross-functional teams, and driving data-driven decision-making. The ideal candidate possesses deep ML expertise, strong analytics foundations, and business acumen, along with significant experience in building and deploying ML systems. Mercury offers a competitive total rewards package including base salary, equity, and benefits.

Requirements

• 5+ years of analytics experience, with 1+ years managing analytics teams
• Deep expertise in SQL, Python, and data modeling
• Hands-on experience with generative AI and agentic frameworks (e.g., LangChain, LangSmith, LlamaIndex, CrewAI, Pydantic, Foundational LLMs, Fine-tuning, DSPy, specialty SLMs)
• Hands-on experience with real-time machine learning: building, deploying, and managing P0 production systems with SRE responsibilities
• Experience building self-service analytics tools and data products
• Strong background in experimentation and causal inference
• Track record of successful zero-to-one product development and launches
• Background in financial services (banking, insurance, accounting, or payments)
• Proven ability to influence strategy and lead cross-functional initiatives

Responsibilities

• Lead a team of 3 senior IC data scientists supporting the Expansion team across bill pay, invoicing, spend management, accounting, credit/lending, and personal banking initiatives
• Design and implement self-service data products that enable teams to answer key business and product questions independently
• Build ML and AI systems that enhance core product experiences, including automated transaction classification and generative AI applications
• Develop comprehensive measurement frameworks and automated reporting systems for new product launches
• Create and maintain sophisticated A/B testing frameworks to evaluate product improvements
• Partner with Product and Engineering leads to establish data infrastructure and ML systems for new product lines
• Create data-driven frameworks for evaluating and prioritizing greenfield opportunities

Benefits

• Base salary
• Equity (stock options)
• Benefits