Data Scientist - Growth

Legora; New York (NY); On-site; USD 120,000 - 190,000; Full time

Job summary

Legora, based in New York, is seeking a Data Scientist for Growth to build scalable data foundations that power go-to-market decisions. You will connect data from CRM, marketing, and product usage, and develop reliable pipelines and dbt models.

You’ll work with RevOps and GTM teams to define metrics such as pipeline, CAC, retention, and expansion, and you’ll deliver dashboards that allow teams to act on insights across the sales, marketing, and customer success functions.

Qualifications

• Strong proficiency in SQL and Python.
• Deep data modelling and analytics engineering.
• Experience modelling growth-side data systems (CRM, marketing, product usage).
• Familiarity with Salesforce or HubSpot is a plus.

Responsibilities

• Own the Growth data model with clean, documented dbt models.
• Bring new GTM data sources into the warehouse and scale beyond the current use case.
• Define and align metrics across pipeline, conversion, CAC, retention, and expansion.
• Collaborate with RevOps and GTM leaders to standardise data definitions.
• Ensure CRM and marketing data quality; surface gaps and fix at the source.
• Build dashboards and reporting that scale across GTM teams.
• Help shape data-team ways of working and tooling.

Skills

SQL

Python

dbt

Dimensional modelling

Analytics engineering

Data modelling

Tools

Salesforce

HubSpot

Job description

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.

As a Data Scientist for Growth at Legora, you'll build the data foundations that help our go-to-market teams make better decisions. You'll work end-to-end: connecting data from business systems, building reliable pipelines and dbt models, defining shared metrics, and answering questions about how we grow.

Your background may be in analytics engineering, data science or data engineering. You enjoy building data models that others can trust and reuse, and working closely with business teams to put that data to use.

You'll be based in our New York office, sitting with the Growth data team. Our go-to-market data is spread across a CRM, marketing automation and messaging platforms, sales engagement and call tools, support tooling, and our own product. Making those systems agree with each other, and with what customers actually do in Legora, is the heart of this job.

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.

We're a Small, Centralised Team Supporting The Whole Company. This Seat Is For Growth. Working Closely With RevOps And The GTM Teams, You'll Help Answer Questions Like

• Marketing: acquisition funnels, attribution and CAC, campaign measurement, and what actually moves enterprise legal buyers.


• Sales & RevOps: what drives pipeline, sales performance and pilot-to-customer conversion.


• Customer Success: account health, expansion and churn signals, and renewals in a category that didn't exist three years ago.


• Lifecycle: getting modelled data back into the CRM and messaging tools, so teams act on it where they already work.

You’ll partner directly with leaders across Marketing, Sales, RevOps and Customer Success who are data-fluent and eager to act on the wealth of data across our business. Your role is to bring structure to that data, uncover insights together, and build the tools and foundations that let them explore questions for themselves, shaping how we sell, where we spend, how we price, and which customers we invest in.

What you will be doing

• Own the Growth data model: turn raw data from our CRM, marketing, messaging, sales engagement and support systems into trusted, documented dbt models that join cleanly to product usage.


• Bring new GTM sources into the warehouse when you need them, and partner with data engineering on anything that needs to scale beyond your immediate use case.


• Work with RevOps and GTM leaders on the metrics that matter (pipeline, conversion, attribution, CAC, retention and expansion), so each has one trusted definition across teams.


• Together with RevOps and Marketing Ops, get modelled data back into the business systems, so Sales, Marketing and Customer Success can act on it in the tools they already use.


• Flag the field and process gaps that make CRM data hard to trust, and help RevOps and Marketing Ops fix them at the source.


• Run the deep dives that move the business: where pipeline leaks, which campaigns create revenue, what wins a pilot, which accounts are at risk or ready to grow. Proactively surface the questions nobody is asking yet.


• Build dashboards and reporting that scale beyond you, so GTM teams can answer their 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.


• Genuine depth in data modelling and analytics engineering: dbt, dimensional modelling, testing, semantic layers, and the judgement to build models others trust and reuse.


• Hands-on experience modelling data from growth‑side business systems, for example:
  
  
  • CRM (Salesforce, HubSpot)
  
  
  • Marketing automation and