Data & analytics

Hire a data scientist in Greece and Cyprus

Modelling with a business case attached, by a practitioner who knows when a simple heuristic beats a model.

Not every company that wants a data scientist needs one yet, and not everyone with the title has taken a model further than a notebook. Done properly, the work changes a daily business decision. In Greek and Cypriot companies it usually starts with:

Demand forecasting that changes what the company orders
Pricing support that changes what it charges
Credit and churn risk that changes who the team calls
Optimisation where the constraints are real: routes, stock and shifts

The data scientists on Hellenic Talent are elite professionals from industry data science teams, top consultancies and quantitative roles in banking and telecoms. They have taken models to production and lived with them, which is a different discipline from building them.

What does a data scientist actually do?

Frame the modelling problem around a measurable payoff, or say why there is none
Size the model to the data you actually have, not to the textbook
Agree the evaluation first, so what counts as good is settled before any model
Explain the model in business terms to the people who act on it
Take models into production with the ML engineer, and keep them honest as data drifts
Leave models your team can run: retrain, monitor and retire

How to choose the right data scientist

What to test in the first conversation, whoever you end up hiring.

Beats the simple baseline
Shows how much a past model improved on a simple rule or last year's average, not only its accuracy score.
Agrees which error costs more
Settles with the business which mistake costs more, such as a missed sale or excess stock, before building anything.
Models on patchy history
Has modelled on the patchy history Greek and Cypriot mid-market companies keep: short series, gaps and changed product codes.