Credit Data Scientist, DOM.RF
We develop still young, but already booming Russian agency mortgage backed securities market by enhancing both in-house and public pricing capabilities and sharing related knowledge. We also build all the quantitative analysis tools used for mortgage securitization decision making. Currently we are looking for a teammate who will analyze borrower behavior and build machine learning models for mortgage loan defaults and prepayments.
Details of day to day tasks are as follows:
Research and development of mortgage instrument pricing models, with focus on calibration and enhancement of credit models for loan portfolios, using both static loan specific and dynamic broad economic factors. This also includes the analysis of real estate market related time series, interest rates, spreads and realized yields dynamics.
Solid technical education, production model building experience and background in credit and interest rate modeling.
Python, SQL, version control (we use git) knowledge is needed.
Financial mathematics knowledge and credit related experience in banks, investment companies are preferred.
Versatile programming know-how and public financial markets exposure are desired.
Linux, Shell, Kubernetes, Jupiter Lab, Latex knowledge, SQL queries tuning experience is also desired.
Strong small team (MSU, MIPT, NES, HSE graduates, Sberbank alumni), office near Arbatskaya or remote as an option.
Market+ compensation, full labor laws compliance, medical insurance.
DOM.RF is an integrated housing development institution, established by a decree of the Government of the Russian Federation in 1997 to promote the implementation of housing policy.
DOM.RF attracts investment and improves the quality and affordability of housing.
|Region||Russia (Россия), Moscow|
|Location||Remote as option|