Data Science
contractors, shortlisted in 72 hours.

Finding data science contractors who
understand the context is harder than it looks.

Data science answers questions from a company's own data: what will demand be, which customers are about to leave, whether the change actually caused the lift, and what the best allocation is under a constraint. That is a different discipline from AI Talent, which builds systems on foundation models, and the two are briefed as one often enough to be worth separating. The sub-desks are applied machine learning, statistical modelling and experimentation, forecasting and demand science, optimisation and operations research, causal inference and measurement, and model deployment and monitoring, the last of which is staffed with the MLOps desk rather than restated here. We screen on whether a model reached production and what happened to it afterwards, because the failure mode is a notebook nobody could deploy and a result nobody could reproduce.

• Specialist-screened for platform depth, not certificates
• Data and analytics-context screening
• 72h from brief to shortlist: every time