Data Scientist, Hebbia
Product
$180-260k
+ New hire equity grant
5 days a week in office
The leading AI platform for finance
Posted today
The leading AI platform for finance
101-200 employees
Posted today
$180-260k
+ New hire equity grant
5 days a week in office
101-200 employees
Company mission
To put capable AI in the hands of 1 billion people by 2030.
Role
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
- 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
Our take
Hebbia is an AI platform that can actually keep up with the pace and complexity of modern decision-making. USed by the world's top asset management, investment banks, law firms, and Fortune 500 companies, Hebbi's "AI-powered analyst" helps team drive investment decisions. Instead of relying on chatbots or basic search tools, Hebbia allows AI agents to break down complicated work into clear, traceable actions so analysts and deal teams have a better way to automate their most time-intensive workflows.
That capability just expanded in a major way too, with Hebbia's acquisition of FlashDocs, a leading generative AI platform for enterprise-grade slide decks and report creation. FlashDocs already automates more than 10,000 slides per day fro top Ai and enterprise companies, and now its technology allows Hebbia users to generate investment memos, board materials, diligence summaries, and branded presentations in just seconds. By combining deep document analysis with automatic artifact creation, Hebbia is tackling some of the most tedious tasks in finance, consulting, an legal work.
This momentum has continues with major industry partnerships, including its recent integration with FactSet, one of the most trusted names in financial data. By bringing FactSet's market, company, an estimates data directly into the platform, analysts can now blend structured financial datasets with Hebbia's unstructured document intelligence in real time. Backed by investors such as a16z, Peter Thiel, Google Ventures, and Index, and already deployed across a third of the world's largest asset managements, Hebbia has quickly positioned itself as the AI platform capable of powering the next generation of knowledge work.
Steph
Company Specialist at Welcome to the Jungle
Meet the team
15 people
Meet Barry, GTM
Our mission
Partner with leading financial institutions to turn complex workflows into AI solutions and make Hebbia indispensable to their success.Company
Funding (last 2 of 3 rounds)
Jul 2024
$130m
SERIES B
Jul 2022
$28.6m
EARLY VC
Total funding: $159.7m
Company 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
Company values
- Cogency
- Compassion
- Running Hard
- Readiness
Company HQ
SoHo, New York, NY
Articles
Leadership
George Sivulka
(Founder & CEO)Founded Hebbia in 2020.
Danny Wheller
(VP of Business, Strategy & Growth)Previously spent 6 years at Palantir, working in Business Development and as the Global Head of Financial Services.
Tom Reeson Price
(VP of Sales)Previously spent nearly 4 years at AuditBoard as a Director/VP of EMEA> Prior to that, he was a Regional Manager of Enterprise at AppDynamics and held several Sales roles at HeadBox.
Jennifer Chittim
(Head of Customer Success)Previously the VP of Global Customer Success at Templafy, the VP of Customer Success & Account Management at Vi and Botify and the Head of CLient Partnerships (Account Management) at Wunderkind.
Aabhas Sharma
(Chief Technology Officer)Previously spent a decade across Sosh, Postmates, and Uber through two acquisitions, rising from Software Engineer to Director of EPD. Most recently, he was CTO of Found, scaling Series A through C.
Tom Navin
(Head of People)Previously spent 8 years at Latch, joining at a People Operations Manager before becoming the DIrector of People Operations and then VP of People.
Jillian Liu
(Head of Revenue Operations)Previously a Senior Director of Revenue Operations at Alloy. Prior to that, they spent nearly 4 years at Nightfall AI, holding Senior/VP Strategy & Operations roles.
Arjun Mahesh
(Head of Design)Previously the Head of Design at Verse and a Product Designer at Stripe.
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