Demonstrate deep technical capabilities and industry knowledge of financial products
Lead components of large-scale client engagements and/or smaller client engagements while consistently delivering quality client services
Understand market trends and demands in the financial services sector and issues faced by clients by staying abreast of current business and industry trends relevant to the client's business
Monitor progress, manage risk, and effectively communicate with key stakeholders regarding status, issues and key priorities to achieve expected outcomes
Requirements:
Undergraduate (4-year degree) or Masters (Computational Finance, Mathematics, Engineering, Statistics, or Physics preferred) or Ph.D. in quantitative topics with at least 2-10 years of relevant experience.
R, SQL, VBA, Statistics (University degree in Maths or Physics or Computational Economics), Credit Banking regulation (EU), MS Office
Working knowledge or academic experience of statistical and numerical techniques (E.g., Monte-Carlo methods, Finite difference methods)
Knowledge of mathematical concepts and domain knowledge related to pricing derivatives for any of the asset classes such as fixed income, equities, credit, interest rates, FX, and commodities
Good hands-on experience in model development/validation/monitoring/audit procedures (including Stress testing, Back-testing, Benchmarking, etc.).
Knowledge of mathematical concepts like Stochastic Calculus, Differential and Integral calculus (ODE/PDE/SDE), Numerical Methods, Linear algebra, Measure Theory. Related to pricing derivatives for any of the asset classes such as fixed income, equities, credit, interest rates, FX, and commodities
Development/Validation/Annual Review of Equity pricing models, Interest Rate Models (HW1F, HW2F, HJM, LMM), Stochastic Volatility (SABR, Heston) model, Local Volatility model (Dupire), frameworks for Volatility stripping and calibration, Bootstrapping of IR curves (Single curve, Multi curve framework), Asset Liability Management (NII, MVPE) and Prepayment Models.
Knowledge of Estimating Idiosyncratic volatility (specific risk) and estimating Beta, Handling missing data in time series, Validating proxy time series.
Strong coding skills in Advanced Python or Java, C++ with combination of Statistical packages in R. Basic knowledge of SQL is expected.
Excellent communication and strong problem-solving skills
Project management and report writing experience
Risk parameter modelling and validation
Credit portfolio modelling and validation
FSO & EU Regulation (CRR, ECB)
German: B2, English: B2
Good-to-have:
Certifications such as FRM, CQF, CFA, PRM
Regulatory knowledge/experience in areas such as Basel, CCAR, and FRTB.
ETRM/CTRM systems experience with knowledge of end-to-end commodity trade lifecycle of power/gas/softs/metals etc.
Pricing/Risk management system knowledge/experience – Calypso, SunGard Adaptiv, Murex, Numerix, Bloomberg, RiskMetrics, Spectrum, EQF, etc.