Hebbia provides an AI platform for finance, legal, and corporate industries, enabling firms to leverage generative AI for complex tasks. Their core product, Matrix, utilizes a proprietary ISD…
AI PlatformCorporateData AnalysisFinanceGenerative AILegalRAGWorkflow Automationhebbia.com
Hebbia
Hebbia provides an AI platform for finance, legal, and corporate industries, enabling firms to leverage generative AI for complex tasks. Their core product, Matrix, utilizes a proprietary ISD…
AI PlatformCorporateData AnalysisFinanceGenerative AILegalRAGWorkflow Automationhebbia.com
HQNew York City, US
Team Size157
Open Jobs3
Total Funding$161M
Latest Fundraise2 years ago
TL;DR
What they do: AI platform for document search, structuring, and workflow automation for enterprise knowledge work
Customers / focus: Enterprise customers in finance, law, government, and pharma
Funding: Raised about $160M total, including a $130M Series B led by Andreessen Horowitz
HQ: New York, NY
Founded: 2020 (listed)
Company Overview
Problem Domain
Enterprise document intelligence and workflow automation for knowledge work
Founded
2020
Industry
Software Development
Funding Track Record
Series A- 2022-09-27
30000000
Company announcement dated September 27, 2022
Series B- 2024-07
130000000
Reported July 2024 at roughly a $700M valuation; participants included GV and Peter Thiel
Investor Signal
“Backed by prominent VCs including Index Ventures and Andreessen Horowitz; participation from GV and notable angel/strategic investors such as Peter Thiel”
Founders
What we do
Join the Team
Data Scientist
On-SiteSan Francisco Bay Area, New York, US
On-Site • San Francisco Bay Area, New York, US
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Who you are
3+ years of experience in product analytics, analytics engineering, or data science at a B2B SaaS company or high-growth startup
You have defined, implemented, and operationalized product metrics from scratch, ideally at a company where the analytics function did not exist yet
Strong in SQL and Python. You can write production-quality transforms, not just ad hoc queries
Experience with modern data stack tools: dbt, Airflow, Snowflake, BigQuery, or similar. You understand data modeling and warehouse architecture
You have built dashboards and reporting that product teams and leadership actually use to make decisions
You understand B2B product analytics: account-level metrics, multi-user workflows, enterprise engagement patterns, and why B2B retention analysis is different from consumer
You translate ambiguous product questions into structured analyses. You do not wait for someone to hand you a spec
Strong product intuition. You care about why users behave the way they do, not just what the numbers say
Clear communicator. You can present findings to engineers, product managers, and executives with equal effectiveness
Experience with enterprise customers in finance, legal, or consulting domains is a plus
Familiarity with usage-based or consumption-based pricing models and the analytics that support them is a plus
Experience using AI/LLM tools to accelerate analysis, build data products, or automate reporting workflows is a plus
What the job involves
Benefits
Start-up equity
Competitive Salary
Office in Downtown NY
Commuter benefits
Flexible PTO
Comprehensive medical, dental, and vision insurance
Daily Catered Lunches
Fertility HRA
Parental Leave
Startup jobs. A lot of them.
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This is the founding hire for product analytics at Hebbia. Today, we do not have a canonical product metrics layer. We do not have clean fact tables around product usage
The person who steps into this role will define what our core product metrics are: what counts as an active user, what engagement actually means, what signals correlate with retention
This is not a dashboarding role. The goal is to shape product decisions with data, not just report on them
You will identify which workflows drive repeat usage, where users drop off, what features move engagement, and what differentiates power users from casual users across our enterprise customer base. You will turn product intuition into data-backed insight
The role sits at the intersection of analytics engineering, product analytics, and data science. You will build the infrastructure and do the analysis. Define the metrics, build the pipelines, create the dashboards, and use what you built to inform the roadmap
Define and implement Hebbia’s core product metrics from scratch: active users, engagement, retention, feature adoption, account health. Build the canonical definitions the entire company uses
Design and build the product analytics infrastructure: fact tables, clean data models, and the analytics layer that sits on top of our product data
Build and maintain executive and product dashboards that leadership and product teams use to make decisions
Write DAGs, transforms, and data pipelines that support analytics. Work with engineering to instrument the product so usage data is captured correctly
Analyze customer behavior across our B2B customer base: account-level usage patterns, workflow adoption, expansion signals, and churn risk indicators
Inform the product roadmap using data. Identify friction in user flows, surface feature adoption patterns, and highlight opportunities for product improvement
Partner with product managers and engineers to translate product questions into measurable data and structured experiments
Establish data quality standards and documentation so the metrics layer you build is trusted and maintained
