Level

Harvey

Data Scientist, Product

Harvey is hiring a Data Scientist, Product for a remote role open to applicants in United States. It pays $155k-$260k a year and Level rates it ; you can apply on Harvey.

Level's read on this job

  • On Level's scale, this data scientist role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting lists this role as remote.
  • Tools and skills the posting cites include SQL, Python and Tableau.
  • Level classifies it as a senior role.
  • Level lists 357 other open roles at Harvey.

AI in this role

Drive product success and measure agentic AI feature performance as a foundational product data scientist at Harvey.

sqlpythontableauab-testing
data-analysisproduct-metricscausal-inferenceexperimentation
Why Harvey

At Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.

This is a rare chance to help build a generational company at a true inflection point. We have strong product-market fit and world-class investor support. We’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.

Our team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.

At Harvey, the future of professional services is being written today — and we’re just getting started.

Role Overview

As a Product Data Scientist, you will be a core member of Harvey's product development organization and one of the foundational members of the Data Science function. You will partner with Product, Engineering, Design, Go-to-Market, and company leadership to define how we measure product success, understand user behavior, and make high-quality decisions in a fast-moving environment.

This role is both strategic and hands-on. You will define north-star and product-level metrics, design experiments and causal analyses, build source-of-truth reporting, and turn ambiguous product questions into clear recommendations. You should be comfortable operating where the data is imperfect, the product is evolving quickly, and the right answer requires both analytical rigor and strong product judgment.

What You'll Do
  • Embed with Product and Engineering teams as a trusted analytical partner, identifying opportunities to improve user experience, adoption, retention, and business impact.

  • Define and maintain core metrics that create a shared understanding of product performance and customer value.

  • Design and evaluate experiments, including A/B tests and causal inference methods, to measure the impact of product, model, and workflow changes.

  • Analyze product usage, customer segments, and go-to-market signals to surface insights, size opportunities, and inform roadmap decisions.

  • Build dashboards, reports, and self-serve tools that help teams answer product questions with confidence.

  • Develop models, forecasts, and analytical frameworks to explain user behavior, detect anomalies, and guide prioritization.

  • Translate complex analyses into clear recommendations for technical, business, and executive audiences.

  • Partner with Engineering and Data teams to improve the infrastructure that powers analytics, experimentation, and decision-making.

  • Establish the standards, practices, and culture for Product Data Science at Harvey.

What You Have
  • 5+ years of experience in data science, product analytics, economics, statistics, or another quantitative field, ideally in a high-growth product company, AI company, research organization, or similarly ambiguous environment.

  • A strong track record of using SQL, Python, and statistical methods to answer product questions and turn analysis into product or business impact.

  • Experience defining new metrics and measurement frameworks from scratch, especially for products where usage patterns, customer value, or success criteria are still being discovered.

  • Deep fluency in experimentation, causal inference, A/B testing, and statistical modeling, with good judgment about when precision matters and when directional clarity is enough.

  • Strong product instincts and curiosity about how users adopt, evaluate, and expand their use of AI-enabled workflows.

  • Excellent written and verbal communication skills, including the ability to influence Product, Engineering, Go-to-Market, and executive stakeholders through clear reasoning and compelling data stories.

  • Comfort creating structure in fast-moving, ambiguous environments and raising the quality of decision-making for the teams.

Bonus

  • Experience with AI/ML products, large language models, developer tools, enterprise software, or products used in complex professional workflows.

  • Experience as an early data science or analytics hire at a hyper-growth startup, including helping define team norms, tooling, and best practices.

  • Experience supporting enterprise or B2B products, including analysis of adoption, engagement, retention, expansion, or go-to-market motion.

  • Familiarity with modern data infrastructure and the practical tradeoffs involved in building reliable analytics in a rapidly evolving product environment.

Compensation

$155,000 - $260,000

Depending on your location, an Applicant Privacy Notice may apply to you. You can find all of our Applicant Privacy Notices [here].

#LI-SB1

Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.

We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

How we rate this

Data Scientist, Product at Harvey rates 60 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data AnalysisProduct MetricsCausal InferenceExperimentationSQLPythonTableauAb Testing

Also common in data scientist jobs at this level

Pay

This job starts at
$155k
Typical data scientist job
$166k

This posting starts 7% below the typical data scientist job. See data scientist jobs

Questions you could be asked

  1. Tell me about a project where data analysis was part of your work. What did you do?
  2. Tell me about a project where product metrics was part of your work. What did you do?
  3. Tell me about a project where causal inference was part of your work. What did you do?
  4. Tell me about a project where experimentation was part of your work. What did you do?
  5. Walk me through how you've used SQL in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Data Analysis, Product Metrics, Causal Inference, Experimentation, and SQL. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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