Data Science
Forecasting, segmentation and experimentation run against your own data — not a generic model bolted on afterward. Results get wired back into the product itself, so a finding in a notebook actually changes what a user sees.
A forecast or an A/B test that lives in a notebook is a finding. The same result wired back into the product — a recommendation that actually changes what a user sees, a forecast that feeds a real inventory decision — is what we build toward.
We run experiments against your own data from day one rather than a synthetic benchmark, because the model that wins on a clean dataset and the model that holds up against your actual traffic noise are frequently not the same model.
You need this if
- —You have data but no one translating it into decisions the business acts on
- —Your A/B tests run but nobody trusts the results enough to act on them
- —You want a recommendation or personalisation system, not just a dashboard
What this covers
- Forecasting & modelling
- A/B testing frameworks
- Recommendation systems
Typical stack
Questions
Do you need a data science team already in place to work with you?
No — we can stand up the whole pipeline, from modelling to wiring results back into the product, or work alongside an existing team on just the parts that need it.
How do you validate that a model is actually working?
Against a held-out set from your real data and, once shipped, an A/B test against current behaviour — a model that looks good in evaluation and one that improves an actual metric aren't always the same model.
Can you build recommendation systems from scratch?
Yes — usually starting with a simpler collaborative-filtering or rules-based approach before anything more complex, since it ships faster and is easier to debug when it's wrong.
Often paired with
At a glance
Let us build somethingworth maintaining
Tell us what you are building and what is in the way. You will speak to an engineer, not an account manager, and leave the call with a straight answer.
Typically replies within one business day · NDA on request