Founding Business Operations

About Datalab

Datalab trains models that read documents reliably at scale. The world's most important information is trapped in PDFs, scans, and files that can't easily be parsed, and getting it out correctly matters. From frontier AI labs processing training data to Fortune 500s like Siemens extracting decades of engineering records, Datalab is where businesses turn to when extraction has to be right.

We're at an 8-figure run rate with a team of 7. Anthropic is a customer. And we have hundreds more across FAANG, frontier AI labs, healthcare, finance, government, and legal. Our tools, chandra, surya, marker, and lift, have 70,000+ GitHub stars and broad developer mindshare. We're backed by founding members of OpenAI, FAIR, and Hugging Face.

Role Overview

Datalab is growing extremely quickly, and as we grow, we outgrow our processes every few months. We're looking for a Founding Business Operations hire to find where the business is straining and fix it — designing, running, and improving the operational machinery underneath a fast-scaling company.

This is a true generalist role, and the target will move as we scale. You'll own whatever the highest-leverage operational gap is at a given moment. Right now, that's our revenue and metrics layer: our pipeline and customer data need a real owner, inbound leads need to be captured and followed up reliably, and leadership needs consistent visibility into how the business and our launches are performing. That's where you'll start and where you'll have the most impact in your first few months. In two or three months the biggest gap may be somewhere else entirely — and you'll be the kind of person who's energized by that, not unsettled by it.

You'll work directly with leadership and partner across sales, engineering, research, finance, and our Chief of Staff. If you're ambitious, analytical, and organized, this is a uniquely rewarding opportunity to help build an AI business from the ground up.

Day to day:

A typical week might look like: running the weekly metrics review and flagging what's off track, sweeping HubSpot so deal stages and activity are current, making sure last week's inbound leads actually got routed and followed up, building a pricing-and-margin model from our usage data, and digging into why conversion dipped on a recent launch.

Own the revenue operations layer (your first priority): Turn HubSpot from a periodic cleanup into a system that stays current — deal stages, contacts, and activity always logged. Make sure inbound leads are captured, routed, and followed up so nothing slips through, and chase stalled deals when they go quiet past target windows. Build the pipeline and funnel reporting that shows what's converting and what isn't.

Own the metrics cadence: Run the recurring rhythms that keep the company on track — the weekly metrics review, company KPI reporting, and product analytics. Understand how initiatives and launches are performing, what's driving conversion and what's not, and keep leadership's view of the numbers clear and current.

Drive the analysis behind key decisions: Own pricing and margin analysis, cohort and retention analysis, and the forward-looking models — usage, cost, revenue — that inform how we price, spend, and grow. You'll partner with our finance function, which owns the monthly close and actuals, so your analysis builds on clean numbers rather than redoing them.

Go where the need moves next: Embed into whichever part of the business is straining, design a process that works, run it until it's reliable, then document and hand it off. Today that's revenue and metrics; as we grow it might be customer operations, planning, or something we haven't hit yet. You'll be the person we point at the newest gap.

Ideal Candidate

You have experience in an analytical, rigorous problem-solving role. You're high ownership, extremely organized, excited about breaking down complex problems and turning them into consistent processes — and comfortable reprioritizing as the company's needs shift.

• 2 - 4 years of strong performance in a problem-solving or analytical role (e.g., consulting, investment banking, strategy and operations)

• Track record of executing major strategic initiatives or owning critical processes/workflows

• Strong organizational and analytical skills (e.g., financial modeling, analytics, managing KPIs)

• Comfortable with ambiguity and shifting priorities — energized by owning whatever the biggest problem is that month

• Entrepreneurial mindset with preference for structure

Bonus points if you:

• Have experience at an early-stage startup

• Have a technical degree (CS, engineering, math, physics) even if you took a non-technical career path

• Have BizOps or RevOps experience at a scaling startup

• Are comfortable with a CRM (e.g., HubSpot) and analytics/BI tools

Interview process

• A 30-minute video call to evaluate fit

• A 1-hour conversation to go deep on your past work

• A paid take-home project (~4-5 hours, $300) — take a hypothetical operational challenge at Datalab, perform analysis, and design a repeatable process

• A 1-hour follow-up to discuss the project and meet the team

At this stage of the company, every interview is somewhat custom, so these phases may be rearranged slightly.