The ideal candidate should be able to use large data sets to find opportunities for business outcome improvement and process optimization using statistics and models. The candidate should have strong experience using a variety of data mining/data analysis methods, building and implementing models, using/creating algorithms and creating/running simulations. The right candidate should have 3-5 years of data science and machine learning experience, Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field.

Key responsibilities include:

• Develop and improve analytical tools for building statistical models and machine learning algorithms;
• Use predictive modeling to decrease credit risk, optimize revenue generation and other business outcomes;
• Collaborate with portfolio risk management to understand company needs and devise possible solutions;
• Research and develop machine learning models for data analysis;
• Coordinate with different functional teams to implement models, monitor and analyze their performance and data accuracy;
• Participation in projects aimed at development and implementation of interactive reports and presentations;
• Develop company A/B testing framework and test model quality;
• Keep up-to-date with latest technology trends;

The successful candidate will be/has:

• HSE / MIPT / MSU or other top university graduate with MA degree in Computer Science, Statistics, Applied Math or related field;
• A deep understanding of statistical techniques and concepts (regression, properties of distributions, maximum likelihood estimators, statistical tests and their proper usage) and experience with applications;
• Knowledge and experience in statistical and data mining techniques (GLM/Regression, Trees, Random Forest, Boosting, etc.) and their real-world advantages/drawbacks;
• Experienced in programming (Python / R / SAS) and databases (Oracle PL / SQL);
• Excellent pattern recognition and predictive modeling skills;
• Advanced or fluent English (spoken and written) is preferred;
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, etc. is preferred;
• Understanding of bank risk management, regulatory requirements (e.g. Basel) is preferred;
• A drive to learn and master new technologies and techniques;

What we offer:

• Full-time position with a competitive salary + performance related bonuses;
• Excellent benefit package (free medical insurance, free gym, educational courses in Sberbank Corporate university etc.);
• Unique opportunity to make an active contribution to the formation of the largest data-driven organization in Russia;
• Excellent working environment within our team (80% HSE / MIPT / MSU graduates);
• Outstanding opportunities to learn and progress in modeling and credit risk management;
• Opportunities to influence and improve Bank’s business and risk strategy.
• Ongoing education in the field of predictive analytics, artificial intelligence and machine learning (corporate trainings, participation in conferences and seminars, etc.)