Data

Product Data and Enrichment Lead

Own the product index: what goes in, how it is described, and whether a match built on it can be trusted.

Location
Remote, UK or India
Type
Full-time
Level
Senior.
Reports to
Chinmay Bhatt, founder and CEO
Starts
From Monday 11 January 2027.
Pay
Fixed base, bonus and share options (ESOPs). We go through all three on the first call.

The role

Every match we make is only as good as what we know about the product being matched. Humotron keeps an index of more than 50,000 wellness products, each described in enough detail to be matched to a person: what it is, what is in it, how much, in what form, what it is meant for and what to be careful about. That index is one of the most important things we own.

Your job is to own it. You will decide what goes in and how it is described, run the pipeline that collects and enriches product data from brands and stores across our markets, and make sure that a recommendation built on it can be trusted. When a brand joins, you make sure its catalogue arrives clean and is understood correctly.

It is a role between data, product and science. You will work with our external advisers, including a pharmacist, on how products are described, and with engineering on how the data is collected and served.

What good looks like

First 30 days

You understand how the index is built today, where the data comes from, and where it is weakest. You have measured its quality in a way we can repeat, and agreed what “good enough to recommend” means.

First 90 days

The pipeline runs on a schedule you trust, with checks that catch problems before a user does. The weakest category has been brought up to standard. New brand catalogues go in by a defined process, not by hand.

First year

The index covers more categories and all of our markets, stays current without heroics, and has a quality record we can show to a brand or an adviser. It is clear what each new source or field costs and what it is worth.

What you will do

  • Own the product data model: the fields we hold, what each one means and the rules for filling it.
  • Run and improve the collection and enrichment pipeline, including crawling, extraction, classification and regular refresh.
  • Use language models and other tools to enrich product data at scale, and build the checks that keep their output honest.
  • Set and monitor quality: accuracy, completeness and freshness, by category and by market.
  • Map products and individual items for sale to the matching rules, so the right thing is recommended for the right reason.
  • Work with our external advisers, including a pharmacist, on ingredients, doses, forms, stated uses and cautions, and on how we word them.
  • Onboard brand catalogues from commerce platforms and keep them in sync.
  • Work with engineering on how the index is stored, searched and served.
  • Document sources, methods and known gaps, so that anyone can see how far the data can be trusted.

What you bring

  • Experience owning a large product, catalogue or content dataset where quality mattered: in e-commerce, search, marketplaces, health or a similar field.
  • Strong practical data skills: Python, SQL or their equivalents, and comfort with data that arrives messy.
  • Experience building or running data pipelines, including web data collection done responsibly.
  • Experience using language models for extraction or classification, with a realistic view of where they go wrong.
  • A habit of measuring quality, not assuming it.
  • Care with detail. A wrong dose or a missed caution is not a small error here.
  • The ability to explain data decisions to people who are not data people.

Nice to have

  • Knowledge of supplements, nutrition, skincare or pharmacy.
  • Experience with product taxonomies or product information systems.
  • Experience with search, matching or recommendation systems.
  • Experience with product data across several countries, languages or currencies.

If you have most of this but not all of it, we would still like to hear from you.

Why join

  • You own one of the things the whole company rests on.
  • Real scale and real consequences: tens of thousands of products, and people acting on what we say about them.
  • A mix of data engineering, product judgement and applied science that is hard to find in one job.
  • Direct access to external expert advisers, and to a founder whose background is in data.
  • Share options, so that you own part of what you help build.

About Humotron

Humotron helps people choose wellness products from their own data. A person connects the tracker they already wear, and we match them to the supplements, skincare, footwear, habits and programmes that suit what their data shows, with the reason for each one. For businesses, the same matching runs inside their own store, practice or benefits programme, and they never see or hold anyone’s health data. Humotron is a wellness service, not a medical one.

Where we are

The product is built. It is live for individuals, and the business products are rolling out now. Humotron Ltd is a new company: founded by one person, built so far with a small development team. These are its first seven hires, and they start in January 2027. We are having first conversations now.

How we work

  • Life comes first. We are remote first, we meet in person once a month, and we use AI so that the work fits inside a reasonable week.
  • Small team, short distances. You work directly with the founder and see the effect of your work the same week.
  • We say what we know and what we do not. That applies to customers, to each other and to this job spec.
  • People’s health data is not ours to be careless with. Privacy is part of how the product is built, and part of every decision.
  • We would rather show than tell: a working preview on a brand’s own catalogue beats a slide about it.

How we hire

  1. 1
    Apply. Attach your CV or add your LinkedIn profile. That is all we need, and a person reads every application.
  2. 2
    First call. Thirty minutes with Chinmay, our founder, on the role and on you. We cover base, bonus and share options.
  3. 3
    Working session. About an hour on a real problem from the role, worked through together. It is not a take-home test.
  4. 4
    Final conversation. Whatever is still open on either side, answered plainly. Then a clear decision, without a long wait.

We are an equal-opportunity employer. If you need an adjustment at any stage, tell us at careers@humotron.com. You will need the right to work in the country you are based in.