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Senior Data Scientist - Product

New York City · New York City, New York, United States

Live, first seen by us 70 days ago
Pay
Pay not listedSimilar roles state $118K–$194K
Work setting
On-site — work setting source
Location type: On-site
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Analytics — team source
Department: Analytics
From the employer’s posting

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
Are you legally authorized to work full-time in the country where this job is based? We may not be able to provide visa/work permit sponsorship for this role. Current authorization to work in this country will be needed to complete the hiring process.
From the employer’s application form

What you’ll work on

Full posting
  • Translate ambiguous business questions into structured analyses and recommendations

  • Define metrics and design experiments to test them and measure shipped impact

  • Model the data needed for analysis in dbt, pulling in new sources as needed

  • Build dashboards and reporting that let the company answer its own questions

  • Run deep-dive analyses and surface questions nobody is asking yet

From the employer’s posting
translate ambiguous questions into structured analyses and clear recommendations
Define the metrics that matter, design the experiments or analyses that test them, and measure the impact of what we ship.
Model the data you need for your work in dbt, pulling in new sources when necessary
Build dashboards and reporting that scale beyond you, so the company can answer its own questions where possible.
Conduct deep-dive analyses on the questions that move the business, and proactively surface the questions nobody is asking yet.

What you’ll bring

All qualifications

Core experience

  • Strong proficiency in SQL and Python.
  • Experience in a product-led or SaaS environment, ideally B2B.
  • Excellent communication skills and the confidence to influence decisions through data storytelling, including pushing back when the data doesn't support what someone wants to do.
  • Hands-on experience with our stack: Snowflake, dbt, Hex, Dagster.
  • Data modelling and analytics engineering (dbt, dimensional modelling, semantic layers, self-service)
  • Prior experience as an early data hire at a fast-growing company, i.e.
Qualification wording
Strong proficiency in SQL and Python.
Experience in a product-led or SaaS environment, ideally B2B.
Excellent communication skills and the confidence to influence decisions through data storytelling, including pushing back when the data doesn't support what someone wants to do.
Hands-on experience with our stack: Snowflake, dbt, Hex, Dagster.
Data modelling and analytics engineering (dbt, dimensional modelling, semantic layers, self-service)
Prior experience as an early data hire at a fast-growing company, i.e. you've built the muscle, not inherited it.

About Legora

Your work will directly influence how we prioritise, how we sell, how we price, and how we build.

In the employer’s words · Read in context · Company website ↗

Apply at Legora

Posting record

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Status in our records
Live
First seen by us
Aug 31, 202670 days ago
Recorded sightings
93
Last seen by us
Nov 9, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

$118K–$194K is typical

The middle half of what similar US postings state. This one doesn’t list pay.

From 3,819 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 70

Up longer than most. Similar jobs usually come down between day 7 and day 57.

From 10,789 similar postings that came down. Coming down is not always a hire.

Legora is hiring

4 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Takes jobs down at a usual pace
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • SQL
  • dbt
  • Snowflake
  • Dagster
Where the posting names them
What you'll need - Strong proficiency in SQL and Python. - Solid grasp of data modelling and what it takes to build analytical work that is reliable and trusted.
- GTM & Customer Success: pipeline analytics, customer health, expansion signals, and retention drivers in a category that didn't exist three years ago. You'll partner directly with leaders across Product, Engineering, Finance, and GTM, most of whom are unusually data-fluent and will happily open a SQL editor with you. Your work will directly influence how we prioritise, how we sell, how we price, and how we build. What you will be doing
If you’re driven by impact, pace, and raising the bar. This is the place. The role As a Senior Data Scientist for Product at Legora you will turn data into decisions. You'll sit close to the business, taking questions end-to-end: shaping the metric, modelling the data in dbt, running the analysis, and making the recommendation. You'll pull in new data sources when you need to. Insights are useful; impact is what we hire for. We're an AI-first data team. We believe the data function should be redesigned around what AI now makes possible, not retrofitted with it, and we want someone excited to help define what that looks like in practice.
- Conduct deep-dive analyses on the questions that move the business, and proactively surface the questions nobody is asking yet. - Model the data you need for your work in dbt, pulling in new sources when necessary, and partner closely with data engineering on anything that needs to scale beyond your immediate use case. - Build dashboards and reporting that scale beyond you, so the company can answer its own questions where possible.
- Genuine depth in at least one of the following, with competence across the rest and curiosity to grow: - Data modelling and analytics engineering (dbt, dimensional modelling, semantic layers, self-service) - Experimentation and causal inference (A/B test design, quasi-experiments, statistical rigour)
- Experience in a product-led or SaaS environment, ideally B2B. - Hands-on experience with our stack: Snowflake, dbt, Hex, Dagster. - Prior experience as an early data hire at a fast-growing company, i.e. you've built the muscle, not inherited it.

Your next step

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

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Has Legora posted this job before?

Yes. We’ve followed 2 other Senior Data Scientist - Product jobs there since August 2026. All 2 are still up.

  1. LondonStill up after 70 days, first seen Aug 31
  2. This jobUp 70 days so far, first seen Aug 31
  3. StockholmStill up after 31 days, first seen Oct 10

Demand for Data Scientist roles

New Data Scientist postings at the employers we follow are down 5% over the last 6 weeks compared with the 6 before.

Weekly new Data Scientist postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 1,408, the most 2,964, and the latest week had 2,139.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under Data Scientist, by the work the posting describes.

Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.

Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.

Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.

US government figures for data scientists

Median yearly pay, May 2025
$120,230
Expected change, 2025 to 2035
34.6% more jobsagainst 3.5% for all jobs

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.

Job description

View original posting ↗

About Us

Legora is redefining how legal work gets done. Not built for lawyers, built with them. We work alongside the world’s best legal teams, who expect excellence, precision, and speed, and we hold ourselves to the same bar.

Our AI-native workspace lets legal professionals move faster, think more clearly, and operate with sharper precision. By analysing thousands of documents in minutes and powering end-to-end workflows, we cut through complexity, teams can focus on what matters: judgment, strategy, and outcomes.

2,100+ customers across 80+ countries trust us, including Cleary Gottlieb, Goodwin, Linklaters, White & Case, Dentons, and Barclays. We’ve scaled to $200M+ in ARR, with teams across Europe, North America and APAC, and continue to expand through acquisitions including Qura, Walter AI, Graceview, Cadastral, and Wexler.

We partner with world-class performers: including Aaron Judge and the New York Yankees, Ludvig Åberg (and his caddie), and campaigns featuring Jude Law.

Joining Legora means three things.

  • We lean in: ownership over titles, outcomes over intentions.

  • We fight for excellence: high standards, direct, ego-free feedback.

  • We grow together: as a team and with our customers.

Mission before ego. Everyone contributes. No one coasts.

If you’re driven by impact, pace, and raising the bar. This is the place.

The role
As a Senior Data Scientist for Product at Legora you will turn data into decisions. You'll sit close to the business, taking questions end-to-end: shaping the metric, modelling the data in dbt, running the analysis, and making the recommendation. You'll pull in new data sources when you need to. Insights are useful; impact is what we hire for.

We're an AI-first data team. We believe the data function should be redesigned around what AI now makes possible, not retrofitted with it, and we want someone excited to help define what that looks like in practice.

There's no single profile we hire for. Some of us are strongest at data modelling and analytics engineering, some at experimentation and causal inference, some at machine learning, some at stakeholder influence. You'll likely be excellent at one or two of these and competent across the rest. That's the bar.

We're a small, centralised team supporting the whole company, hiring for the person, not the seat. Depending on your strengths and where we have the biggest gap when you join, you could be embedded primarily with:

  • Product: instrumentation, feature adoption, user behaviour, A/B testing, shaping the roadmap with PMs and designers.

  • Finance & RevOps: ARR, NRR, forecasting, board reporting, pricing analytics across a 40-country footprint, and unit economics for an AI-native product.

  • Growth & Marketing: acquisition funnels, attribution, campaign measurement, lifecycle analytics, and what actually moves enterprise legal buyers.

  • GTM & Customer Success: pipeline analytics, customer health, expansion signals, and retention drivers in a category that didn't exist three years ago.

You'll partner directly with leaders across Product, Engineering, Finance, and GTM, most of whom are unusually data-fluent and will happily open a SQL editor with you. Your work will directly influence how we prioritise, how we sell, how we price, and how we build.

What you will be doing

  • Partner with stakeholders across Product, Finance, GTM, Growth, and beyond to translate ambiguous questions into structured analyses and clear recommendations.

  • Define the metrics that matter, design the experiments or analyses that test them, and measure the impact of what we ship.

  • Conduct deep-dive analyses on the questions that move the business, and proactively surface the questions nobody is asking yet.

  • Model the data you need for your work in dbt, pulling in new sources when necessary, and partner closely with data engineering on anything that needs to scale beyond your immediate use case.

  • Build dashboards and reporting that scale beyond you, so the company can answer its own questions where possible.

  • Help shape how the data team operates as we scale: standards, tooling, ways of working.


What you'll need

  • Strong proficiency in SQL and Python.

  • Solid grasp of data modelling and what it takes to build analytical work that is reliable and trusted.

  • Excellent communication skills and the confidence to influence decisions through data storytelling, including pushing back when the data doesn't support what someone wants to do.

  • Genuine depth in at least one of the following, with competence across the rest and curiosity to grow:

    • Data modelling and analytics engineering (dbt, dimensional modelling, semantic layers, self-service)

    • Experimentation and causal inference (A/B test design, quasi-experiments, statistical rigour)

    • Machine learning and applied data science (forecasting, prediction, segmentation, evaluation)

    • Product analytics and metric design (funnels, cohorts, adoption frameworks, North Star metrics)


Nice to have

  • Experience in a product-led or SaaS environment, ideally B2B.

  • Hands-on experience with our stack: Snowflake, dbt, Hex, Dagster.

  • Prior experience as an early data hire at a fast-growing company, i.e. you've built the muscle, not inherited it.

Most importantly, you are someone who

  • "Gets stuff done" and understands building a $10bn company isn't always glamorous and takes hard work and long hours.

  • Thrives in a fast-paced environment where the answers aren't always clear and processes are few.

  • Is genuinely domain-curious. You don't need to have worked on every part of a business, but you should be excited to.

 

Legora is an Equal Opportunity Employer

At Legora, we believe great teams are built on diversity of thought and experience. We’re proud to be an equal opportunity employer and committed to creating an inclusive, high-performance culture where everyone can do their best work. We welcome people of all backgrounds and don’t discriminate based on race, color, religion, national origin, gender, gender identity or expression, sexual orientation, age, disability, veteran status, or any other characteristic protected by law.

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New York City, New York, United States

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