Lead - Market Risk Analytics - Bank

Job Description:

- We recruits quantitative research associates for the Risk Analytics Department. The ideal candidate will be actively involved in market risk modeling/statistical analysis of our portfolios for the Market Risk Department.

- This includes periodic updating of risk model/benchmark parameters with recently available market/positional data.

- The ideal candidate will have a strong quantitative background and would require an understanding of traded products, a grasp of risk methodologies and the underlying data challenges, as well as an appreciation for the technical architecture around market risk management.

- Strong problem-solving abilities, solid writing, and oral presentation skills are desired.

- The candidate should be able to adjust to multiple demands of the business and should be willing to learn and evolve along with the role.

Skills Required:

- 6+ years of work experience in quantitative modeling, Risk Management, algorithmic trading, global markets, or any other quantitative/Data Science field.

- Understanding of risk management concepts such as VaR (value-at-risk), Stress tests, market risk modeling, Incremental Risk Charge for credit products, back-testing, and the risk representation of various portfolios.

- The candidate needs to be familiar with statistical techniques viz. Regressions Analysis, Hypothesis testing, Time-series modeling, Volatility modeling et al.

- Strong quantitative and analytical skills and ability to work with diverse cultures in a global team.

- Strong knowledge of financial traded products e.g., derivatives and their pricing.

- Knowledge and hands-on experience in one of the programming languages R, Python, MATLAB, C# or C++ is strongly preferred.

- Excellent communication skills (Oral and written). Ability to communicate and present logically, precisely and in simple manner, complex and technical issues.

- Attention to details and ability to work under pressure and cope with a fast-moving environment.

Required Qualifications:

Graduate/Under-graduate/Advance degrees in finance, mathematics, physics econometrics, engineering, or other quantitative subjects.

- Candidates should have a strong theoretical foundation in mathematics, quantitative finance, and derivatives.

- Knowledge and hands-on experience in one of the programming languages.

Desirable Skillsets:

- PRM/FRM, CFA, CQF certification is an advantage.

- Quantitative modeling experience in Finance/ Data Science

- Knowledge of risk mitigation practices and experience with Basel II/III/IV rules will be considered advantageous.

- Experience in AI, ML, NLP, Big Data Analytics, Tableau is an advantage.