Hire pre-vetted Data Scientists

Most companies that try to hire a data scientist end up sorting through hundreds of generalist profiles for $80/hour.

Cortance exists because that process is broken. Every data scientist on this platform has been verified through actual project delivery. Not only interviews. Not take-home assignments. Real commercial projects with real clients, tracked over months and years. When you hire a data scientist through Cortance, you see exactly what they’ve built, how long they’ve used each technology, and what industries they’ve worked in. No guesswork.

What's actually in the toolkit?

The specialists here cover predictive modelling and forecasting, classification, clustering, anomaly detection, recommendation engines, and NLP. Core stack: Python, scikit-learn, XGBoost, LightGBM, PyTorch, and TensorFlow, plus Pandas and SQL for the unglamorous data-wrangling half of the job. Average experience across the roster is about six years of hands-on delivery, not raw career length since graduation. They don't stop at a notebook, either. Dockerfiles, CI/CD, model versioning with MLflow, and drift monitoring after launch are part of the job description here, the parts that turn a demo into something running against real traffic.

Match by industry before the first call

Fintech shows up often: credit risk modelling, trading automation, financial data analysis. Healthcare too: medical image classification, patient data analysis, biomedical document processing. Agritech is a speciality for a few, built around drone and satellite imagery for yield forecasting and crop health monitoring. Add defence, manufacturing, gaming analytics, and sports tech to the list, plus general SaaS products for teams that need forecasting or dashboarding rather than a niche vertical. Industry history is visible on every profile, so you match before you reach out instead of finding out three weeks in that nobody on the shortlist has touched a regulated dataset.

Recent work from this network

Just a few examples:

1. Precision agriculture. Michael Y. built a geo-temporal drone image alignment method for SeeTree that automated 85 percent of the company's data processing pipeline, then followed it with a separate anomaly detection system for crop health monitoring from drone imagery.
2. Defense navigation. Alexander C. developed visual inertial navigation for GPS-denied drones, reaching about 4 meters of error on 1 km simulated missions and 2 to 5 percent positional error in real flight on Raspberry Pi hardware.
3. Fraud detection. Viktoriia A. built a semi-supervised learning system for a blockchain platform that flags malicious transactions inside a highly imbalanced dataset, deployed with MLflow and MongoDB.

Generative AI work is already part of the Data Scientist's job

Our expert Viktoriia A. not only heavily uses GenAI tools in her work, as most engineers do, but also built the fraud detection system above and has run a research project establishing best practices for production-grade LLM applications: prompt engineering experiments, a Retrieval-Augmented Generation pipeline, and an evaluation framework for checking output quality before it ships. If your project builds on top of foundation models rather than training one from scratch, there's a profile matched for that. More broadly, data scientists across the field increasingly pair traditional modelling with AI-assisted tooling to move faster without skipping validation, and this network is no exception.

Share your requirements through the platform or with a hiring manager directly, and Cortance's matching system scores candidates against your stack, domain, seniority, and availability, then delivers a shortlist within 30 minutes to be able to complete a hire within two days.

Our data scientists work remotely on a flexible or long-term basis and are based mostly across Ukraine, Portugal, Spain, and Georgia, which overlaps well with EU and US East Coast hours.

If you need a data scientist who can start moving on real data in week one, not month three, the profiles are below.