Senior Data Scientist, Product Analytics

Fora•New York City, NY

1d•Onsite

About The Position

Fora is hiring a Senior Data Scientist to help us build and deliver delightful product experiences to our advisors and their clients. As our product organization grows, we're looking for someone to raise the bar on how we measure, experiment, and ship products. Fora operates in a dynamic, 3-sided marketplace. As an early member of the team, you'll work on a range of products, from the core booking platform to new, AI-powered experiences. This is a foundational role on the Data Science & Analytics team. You'll operate as a strategic partner to Product, Engineering, and Design, helping drive decisions around roadmap prioritization, feature investment, and what we build next.

Requirements

5+ years in product data science, product analytics, or consumer analytics.
Experience at consumer or marketplace companies preferred.
Experience designing and analyzing product experiments, including causal inference techniques.
Experience building predictive models and applying machine learning techniques.
Advanced SQL skills are essential.
Proficiency in Python or another scripting language preferred.
Hands-on experience with a modern cloud data stack (e.g. Airbyte, BigQuery, dbt, Hex, Omni, or equivalents) and data modeling best practices.
Experience using LLM tools (e.g. Claude Code, Cursor, OpenAI Codex) to accelerate analysis and prototyping.
Strong communication and storytelling skills.
Deeply curious with a drive to learn.
Pragmatic. Looking for real world business impact, not a science project.
A collaborative and empathetic mindset with experience supporting and leveling up your peers.

Responsibilities

Lead deep analyses of product usage and advisor behavior that shape product features and roadmap prioritization.
Own the full lifecycle of product data — from instrumentation and event definitions through to actionable insight — partnering with data engineering along the way.
Design and analyze experiments across core product surfaces, while defining best practices for the company.
Collaborate with product, engineering, and design partners to develop product roadmaps, launch features, and measure success.
Build models to predict user behavior and deliver personalized product experiences.
Raise the bar across the data team — mentor peers, establish best practices, and shape the team's processes, tools, and standards.