Job Title : Sr Quantitative Risk Mgmt Analyst
Location: Bangalore KA
Duration: Full Time/ Permanent
Job Description :
- Principal Accountability
- Develop C++ frameworks one-by-one covering the mentioned asset classes, pricing, margin computation, scenario generation, and liquidity evaluation.
- Design, coding, debugging.
- Cooperate with other developers.
- Use financial and mathematical knowledge for formulation and analysis of the existing and new models.
- Bring this to the stage, where C++ design and implementation can be applied.
- Cooperate with quants. Learn new related subjects. Reading, making reports, experimenting.
- Develop C++ and Java QA tests. Formulate and develop stress tests.
- Design, coding, debugging.
- Participate in automation and adaptation to Clearing Technology Department. Write scripts. Deliver. Make bamboo plans. Review production issues related to delivered software.
Experience :
- Incumbent must have at least four years of experience in financial analytics combined with day-to-day participation in related C++ projects desirably in multi operating system environment.
- 4 + years of intense C++ recent development. Flexibility with the Standard C++ algorithms. Familiarity with C++ 11, 14. Windows Microsoft Visual Studio C++ (one of 2010, 2013, 2014 2015).
- UNIX (desirably Linux) experience with GCC 4.8. - 4.9
- Practical experience with C++ Boost, C++ QuantLib, or C LAPACK. Knowledge of other C++ libraries will be considered.
- Familiarity with Google tests, Java and JUnit tests, JNI, Eclipse is a big plus.
- Operational experience with Git, SVN, CVS, or Perforce.
- 1+ year of work and flexibility with writing UNIX shell, Python, Ruby, or Perl programs.
- Knowledge of Bamboo or TeamCity, Sonatype Nexus or Apache Archiva is a plus.
- Knowledge of relational databases and SQL is a plus.
- Financial analytics (4+ years of work), no arbitrage options pricing models, risk models, portfolio optimization. Asset classes: IRS, FX, CDS, Swaptions, Futures, Commodities.
- Two years of work with Monte Carlo, optimization methods, correlation analysis, discretization with trees and lattices. Flexibility with statistics, probability theory, linear algebra, and functional analysis.
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