Data scientist / Machine Learning Engineer (offline)

Risk Service is one of the most important services that is responsible for automatic analysis of the client data and making a decision about issuing a loan. It's implemented in NET, collaborates with R (run scoring models) and is integrated with tons of 3rd party services. We are actively working on improving existing risk engine (new rules and score models, integration with new services, etc.).

You will be responsible for building ML models, processing and analysis of large data array, construction and automation of management reporting.

Main requirements:
• Strong math skills and experience, particularly in the theory of probability and mathematical statistics, and discrete mathematics, logic and algebra.
• Deep knowledge of the SQL language.
• Experience with Python libs (Pandas, Numpy, Scipy, Scikit-learn, Flask).
• Experience with Computer Vision.
• Analytical mind.

Desired skills:
• Experience with Hadoop ecosystem and NoSQL databases.
• Experience with Docker/deploying ML models to production.
• Knowledge in financial analysis/credit scoring.

Benefits:
• Gym and sports program (football, volleyball, etc.).
• Corporate massage therapist.
• Сonferences сourses and trainings (Paid).
• Flexible working schedule (09:00-11:00 to 18:00-20:00).
• Pleasant buns in the form of corporate events and teamwork, syrups, fruit, cookies, ice cream.
• Lounge with exercise machine, wall bars, table football and tennis, Xbox.
• Vacation days (24 calendar days / year), sick leave.
• Comfortable, modern office in Pechersk district.

Product’s Achievements:
• Regular users of more than 800 000 clients.
• More than 11 billion UAH were provided to our clients.
• For the first time to fill out an application for an online loan, the client of our service needs approximately 8 minutes.
• Our system processes the application and makes a decision in less than 1 minute.

CV review period is 14 calendar days. In case of a positive decision, we will contact you during this time to arrange an interview.