The Asset Management (AM) of Raiffeisen Bank provides institutional and individual investors with investment and advisory solutions, with strategies spanning asset classes, industries and geographies.
We help our clients navigate today’s dynamic markets and identify the opportunities that shape their portfolios and long-term investment goals. We extend these capabilities to the leading pension plans, wealth funds, banks, insurance companies, financial institutions, corporates, individuals and family offices.
• Bachelor or Master level qualification in a computer science and/or engineering, physics are preferred.
• Strong development skills.
• Strong communication skills and an ability to articulate complex software engineering problems and mathematical concepts.
• Advanced programming skills in Python. Some knowledge of R, C++ or Java. Experience with databases. (PostgreSQL is preferred).
• Prior experience in developing algorithmically complex applications and an ability to transform concepts and ideas into robust software.
• Solid understanding of statistics, linear algebra and calculus
• Familiarity or at least an interest in financial markets and quantitative investment approaches
Within AM, quants will be responsible for the design, development and maintenance of the QIS strategies used as an investment vehicle for AM & Capital Markets clients.
Quants will help to build robust cross asset backtester to test different investment ideas, help to support strategies in the productions and be “goto” people for any issues related to the QIS platform. Quants will also help to backtest new ideas, design scalable systematic strategies across all asset classes, write optimizations and machine learning algorithms to extract alphas (or create smart betas) from financial markets by using alternative data sets. Quants will work directly with Co-head of AM on those projects and help him to manage systematic funds.
The ideal candidate is someone who is passionate about the financial markets. He or she will actively participate in all phases of quant development lifecycle: analysis, design, development, testing, release, production support.
- flexible schedule;
- excellent benefits (discounts on corporate products, canteen and cafe);
- professional training courses (in incl. coursera. udemy etc.) and conferences in Russia and abroad;
- opportunity to choose any computer and additional equipment and work on your own device.