Analytics Lead, Full Stack

About This RoleAI processing…

Key Responsibilities

• 1
  Own and prioritize the analytics portfolio for a significant product or business area, operating with a business owner mindset to define success, identify investment opportunities, recommend actions, and measure impact across customer experience, growth, risk, and profitability.
• 2
  Lead complex analyses that balance growth, credit performance, customer experience, and unit economics.
• 3
  Translate analytical findings into clear and compelling narratives and business cases that help leadership make informed decisions.
• 4
  Tackle ambiguous problems by identifying the core hypotheses and designing actionable experiments to validate product-market fit and economic viability.
• 5
  Lead through influence across Product, Engineering, Finance, and Revenue, building alignment around important decisions without formal authority.
• 6
  Build scalable data models, metrics, dashboards, and AI-assisted analytical workflows that improve access to trusted insights while maintaining rigorous validation, reproducibility, and data governance.
• 7
  Raise the impact of the analytics organization by mentoring analysts and developing reusable analytical practices and tools.

Requirements

• A General Manager mindset, strong product and credit risk judgment, and a track record of proactively identifying high-impact opportunities.
• Strong understanding of the consumer lending and credit industry, including lending economics, portfolio performance, and credit metrics. The strongest candidates will bring experience across both risk and product and understand the tradeoffs among growth, credit performance, customer experience, and profitability.
• The ability to perform complex analyses and translate the results into clear, actionable business recommendations.
• Exceptional communication and influencing skills across technical and non-technical audiences, including senior leaders.
• 6 or more years of experience in a cross-functional analytical role, with demonstrated impact on significant product, risk, or business decisions.
• Advanced SQL and Python skills, including statistical analysis, experimental design, and practical experience with A/B testing.
• Demonstrated curiosity and a growth mindset, with hands-on experience using AI-powered tools such as Cursor, Claude, or similar assistants to accelerate analysis, automate workflows, enhance problem-solving, and advocate for AI adoption across analytical workflows.
• The ability to independently prioritize a roadmap, manage multiple workstreams, and mentor other analysts.
• A bachelor’s degree in a quantitatively rigorous field—or equivalent practical experience. An advanced degree is a plus.

Perks & Benefits