Product Analytics, Data Scientist

Farsight AINew York City, NY
Hybrid

About The Position

Farsight is the agentic AI platform for financial services, currently helping investment banks and private equity firms fully automate entire, highly nuanced workflows. Today, institutions will spend 80% of their time gathering information for and creating first drafts of materials by hand before iterating on and refining their decks, models, and pitches. We not only give them that time back to focus on what is important, but we also bring new insights and knowledge to their materials that they wouldn’t be able to uncover without the help of our financial-focused AI. Our Team Our team has had a wide range of experience that uniquely equips us to capture this massive opportunity. Our team comes from leading financial institutions like Evercore, General Atlantic and Menlo Ventures, supercharged by scalable engineering and AI skills from companies including Amazon, Hugging Face and the MIT Media Lab. We've learned the ins and outs of building successful startups from previous work as founders and founding engineers. We focus on hiring the best so that we can become the best, so we hope you apply! We are entirely based in Manhattan, New York City, and are in-person 4 days a week (except Fridays, which are remote).

Requirements

  • 3+ years in product analytics, data science, or a related quantitative role
  • Strong SQL and Python skills — you can get your own data without waiting on an engineer
  • Experience translating data into clear narratives for non-technical stakeholders
  • Comfort working in ambiguous, fast-moving environments with limited existing infrastructure
  • Curious, self-directed, and energized by building from scratch

Nice To Haves

  • experience in financial services, AI products, or early-stage startups

Responsibilities

  • Synthesize customer feedback, usage data, and behavioral signals into product insights
  • Build dashboards and reporting infrastructure that surface what's working and what isn't
  • Partner with the strategy team early on to understand and quantify customer pain points
  • Define and track the metrics that matter for an agentic AI product — including non-deterministic outputs
  • Inform product roadmap and engineering priorities with data-driven recommendations
  • Build the analytics foundation that scales with the product and team

Benefits

  • Meaningful equity at Series A
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