Data Scientist, Product

Mirage•New York, NY

2d•$120,000 - $180,000•Onsite

About The Position

Mirage is an AI video company focused on making creation dramatically easier. Our team tackles some of the hardest creative and technical challenges in generative media. We get to rethink how people collaborate with AI that can actually do creative work with them—defining entirely new interaction paradigms for AI-native video tools. We make that possible by building multimodal agents that turn creative direction into edits, rendering engines that composite multiple layers of video and graphics, and generative video models trained from the ground up that create new media when needed. All of this comes together in Captions, our creative workspace for generating, editing, and designing video. The technology behind Captions is now available more broadly: Tesseract gives any AI agent native video-editing capabilities, while developers can integrate our models into their own products through APIs. Explore our work Captions — Our flagship creative workspace Tesseract — Our professional video engine for AI agents Research — The foundation models we build in-house Updates — The latest from Mirage TechCrunch, Forbes, Fast Company — Press Our Investors We’re very fortunate to have some the best investors and entrepreneurs backing us, including Index Ventures, Kleiner Perkins, Sequoia Capital, Andreessen Horowitz, General Catalyst, Uncommon Projects, Kevin Systrom, Mike Krieger, Lenny Rachitsky, Antoine Martin, Julie Zhuo, Ben Rubin, Jaren Glover, SVAngel, 20VC, Ludlow Ventures, Chapter One, and more. Please note that all of our roles will require you to be in-person at our NYC HQ (located in Union Square) About the Role We’re hiring two Product Data Scientists to ground the decisions behind Captions in clear metrics, rigorous analysis, and a deep understanding of how people use the product. One person will embed with our iOS team and the other with our web team, working day to day with Product, Design, Engineering, and Data Engineering. You’ll be present as questions and product ideas take shape, not brought in after launch to explain what happened. You’ll define success, evaluate experiments, investigate user behavior, and turn ambiguous findings into clear recommendations. You’ll then follow them through by communicating the reasoning, building alignment, and making sure decisions result in action. We care about analytical depth, product judgment, and the ability to make a team more rigorous. We work AI-first: Codex and Claude Code are part of the everyday workflow, and you’ll be expected to validate the work they help produce.

Requirements

A bachelor’s degree in a behavioral or quantitative field, or equivalent practical experience, with a strong statistical foundation.
3+ years of experience in product analytics or product data science, acting as the analytics voice within a consumer product team.
High proficiency in SQL and either Python or R, including libraries such as pandas, NumPy, SciPy, or Tidyverse, with strong data-model reasoning and the ability to write and understand analytical code.
Experience applying statistical analysis, experimental design, causal inference, and machine learning to product problems, with the judgment to choose an appropriately simple method and translate the result into a specific, actionable recommendation.
Fluency using AI across exploration, analysis, experimentation, and modeling, including providing relevant context, debugging incorrect outputs, and converting repeatable work into reliable workflows.
Strong written and verbal communication skills, including the ability to explain uncertainty and limitations, persuade technical and nontechnical partners, and lead decisions through to action.

Nice To Haves

Experience with iOS or web analytics, including instrumentation, release measurement, funnels, or experimentation.
Experience with dbt, cloud data warehouses, and large event datasets.
Experience applying product analytics to a consumer creative product.
Experience building reusable AI-powered data science systems, such as agents, orchestration layers, automated analyses, or evaluation and review workflows.
Strong user empathy, curiosity, and excitement about learning in a fast-moving environment.
A proactive, independent working style: you pursue leads, find the people and context you need, operate through ambiguity, and follow work through from recommendation to action.

Responsibilities

Embed with either the iOS or web team from planning through launch, defining hypotheses, success criteria, core metrics, and measurement approaches while partnering with Engineering and Data Engineering on instrumentation and data quality.
Lead analysis to uncover patterns in product and user behavior, prioritize high-leverage opportunities, recommend actions, and measure realized impact.
Design and evaluate A/B tests and other product measurements, setting appropriate guardrails and turning results into decisions.
Create executive-ready visualizations, dashboards, experiment readouts, and decision memos that drive alignment on what happened and what the team should do next.
Build machine learning and statistical models to solve core user problems, improve the product experience, and deliver measurable user impact.
Design AI-native tools, systems, and automated workflows that accelerate data science and analytics while enabling self-service capabilities.