Data Scientist - Growth

Legora • New York, NY

8d • $131,750 - $178,250 • Onsite

About The Position

As a Data Scientist for Growth at Legora, you will build the data foundations that help go-to-market teams make better decisions. You will work end-to-end to connect business-system data, build reliable pipelines and dbt models, define shared metrics, and answer questions about how the company grows. The role is suited to someone with a background in analytics engineering, data science, or data engineering who enjoys building trusted, reusable data models and working with business teams to put data to use.

Based in Legora’s New York office with the Growth data team, you will help reconcile data across CRM, marketing automation and messaging platforms, sales engagement and call tools, support tooling, and the product. You will work closely with RevOps and leaders across Marketing, Sales, and Customer Success to structure data, uncover insights, and build tools and foundations that help teams explore questions and make decisions about selling, spending, pricing, and customer investment. Legora describes its data team as AI-first and seeks someone interested in helping define how the data function can work with AI.

The role covers Growth data modelling and GTM analytics, including acquisition funnels, attribution, campaign measurement, pipeline, sales performance, pilot-to-customer conversion, account health, expansion, churn, and renewals. You will also help return modelled data to business systems so teams can act on it in the tools they already use, improve data quality at the source, and build scalable dashboards and reporting. You will contribute to the standards, tools, and ways of working of a small, centralised data team as it scales.

Requirements

• Strong proficiency in SQL and Python.
• Depth in data modelling and analytics engineering, including dbt, dimensional modelling, testing, semantic layers, and judgement to build models others can trust and reuse.
• Hands-on experience modelling data from growth-side business systems, such as CRM, marketing automation and messaging, sales engagement and conversation intelligence, support, or in-app messaging platforms.
• Understanding of the data-quality quirks of business systems, including overwritten fields, missing history, duplicate contacts, and opportunity stages with inconsistent meanings.
• Solid grasp of go-to-market analytics, including funnels, attribution, pipeline and forecasting, cohort retention, and net revenue retention.
• Excellent communication skills and confidence influencing decisions through data storytelling, including pushing back when data does not support a proposed action.
• Able to work in an onsite environment and thrive in a fast-paced setting where answers may be unclear and processes are limited.
• Genuine curiosity about the legal sector and how law firms buy; prior experience selling to law firms is not required.
• Willingness to take ownership and work hard, including long hours as needed to build a company.

Nice To Haves

• Experience in B2B SaaS with an enterprise, sales-led motion.
• Hands-on experience with Snowflake, dbt, Hex, Dagster, dlt, or Salesforce.
• Experience with reverse ETL or data activation, using a tool such as Hightouch or Census, or custom-built syncs.
• Experience with experimentation or modelling on go-to-market questions, such as campaign holdouts, uplift, propensity, or forecasting models.
• Prior experience as an early data hire at a fast-growing company, building data capabilities rather than inheriting them.

Responsibilities

• Own the Growth data model by turning raw data from CRM, marketing, messaging, sales engagement, and support systems into trusted, documented dbt models that join cleanly to product usage.
• Bring new go-to-market data sources into the warehouse and partner with data engineering on work that needs to scale beyond the immediate use case.
• Work with RevOps and go-to-market leaders to define shared metrics for pipeline, conversion, attribution, customer acquisition cost, retention, and expansion.
• Work with RevOps and Marketing Ops to make modelled data available in business systems so Sales, Marketing, and Customer Success can act on it in their existing tools.
• Identify CRM field and process gaps that undermine data trust and help RevOps and Marketing Ops address them at the source.
• Conduct deep dives into pipeline leakage, revenue-driving campaigns, pilot wins, account risk, and growth opportunities, and proactively surface unanswered business questions.
• Build scalable dashboards and reporting that enable go-to-market teams to answer questions independently where possible.
• Help shape the data team’s standards, tooling, and ways of working as it scales.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed