Description
WHY THIS ROLE
We're building the world model for a resilient global economy.
The global economy runs on physical assets: fabs, plants, mines, warehouses, data centers, pipelines. A drought, a port closure or a failed supplier moves through those assets into company earnings, and from there into markets. Our mission is to make the global economy more resilient by translating the physical world into financial impact.
We start with asset-level intelligence for financial markets. Kepler maps the physical assets of every company we cover, models what each one produces and earns, and connects them to the company's financials and to each other — who supplies whom, where revenue concentrates, and what can be substituted.
On that foundation, we layer risk. Physical risk is the first layer, and it's live today: drought, heat, flooding and wildfire, turned into asset-level, dollar-denominated, point-in-time Earnings-at-Risk built to sit next to a Bloomberg feed on an investor's desk. Supply-chain dependencies come next, then geopolitical concentration, with more layers to follow.
We're already working with 3 of the world's top asset managers (over $30 trillion AUM).
The product is live and the pilots are multiplying — asset managers, hedge funds, private equity. Every pilot means running companies through our pipeline, checking every output, and turning results into something a customer can act on: a dataset, a chart, a case study. Every monthly release means checking millions of numbers before they reach a customer's models, and every new risk layer adds more.
Today our founding team does all of that alongside building the product. That's what this role will tackle. You'll be one of the first members of our technical staff, and the person who makes sure what we ship is right.
WHAT YOU'LL OWN
The pilots. Customer pilots and custom analyses, end to end on our pipeline: scope it with the team, run the companies, produce the outputs, get them reviewed and delivered.
Data quality. The checks every release passes before it reaches a customer. You'll turn manual QA into automated tests, and own the standard.
Customer-ready data. Sample datasets, trial packs and Snowflake deliveries — prepared fast, and right.
The feedback loop. Every issue you find goes back into the pipeline so it doesn't come back.
Exactly how each of these looks is still being written. You'll have a real hand in writing it.
WHAT WE'RE LOOKING FOR
1–3 years writing production Python and SQL — in data engineering, analytics engineering, data science or a technical analyst role. Strong new grads with real projects are welcome.
You catch the number that's wrong. Attention to detail is the one non-negotiable here.
You take a task from "here's a company" to "here's a validated output" without waiting on anyone.
Curiosity about how businesses and markets work. If you can't read a 10-K yet, you'll want to learn.
High agency, low ego. You'd rather fix the check than argue about who broke it.
And you're someone we'll want to build alongside for thousands of hours.
NICE TO HAVE (GENUINELY OPTIONAL — YOU DON'T NEED ALL, OR ANY)
* Pipeline orchestration, Snowflake or dbt, or data-testing frameworks.
* Geospatial data (GeoPandas, rasters, remote sensing).
* Finance coursework, an internship, or a real interest in markets.
* Any customer-facing work.
* We'd rather hire someone very smart and very curious who can grow into the role than someone who ticks every box.
WHAT YOU GET
* $120K–$145K base + 0.1–0.3% founding-level equity. (placeholder — not confirmed; check vs. Vidyut's band)
* Health-insurance reimbursement (QSEHRA) and a real commitment to grow benefits at every raise and milestone.
* An awesome office space to work from in San Francisco.
* A seat next to the founding team on work that lands on the desks of the largest institutions in the world, with room to grow into engineering, data science or customer-facing work as we scale.
OUR VALUES
Curiosity. Pragmatism. Empathy. Transparency. Care.
PROCESS
1. Intro call with CEO · 15 min — mutual fit
2. Intro call with CTO · 30 min — your technical background
3. Deep dive with the founders · 60 min — your background, role by role
4. Working Session + Success Plan · 120 min (2 parts) — run a small pilot on a sample of our data, find what's wrong in the outputs, and present both; then discuss how you'd succeed in the role
5. References
6. 1-Day Working Interview — assessing long-term fit together
7. Offer
HOW TO APPLY
Fill in the form here and upload your CV. Questions? Email careers@keplerdatalabs.com [careers@keplerdatalabs.com]