Associate - Market Risk Control

 
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In Scope of Position based Promotions (INTERNAL only)
Job Title-
Associate - Market Risk Control
Location- Mumbai, India
Role Description
Market Valuation and Risk Management (MVRM) is responsible for managing market risk and ensuring fair value assessment of Books & Records within Deutsche Bank. The primary market risk objective is to ensure that business units of the bank optimize the risk-reward relationship and do not expose it to unacceptable losses. We work closely with risk takers, risk managers and control and support groups in the process to ensure these objectives can be met.Market Data Strategy and Analytics (MDSA) is a function within MVRM that is responsible and accountable for the procurement, analysis and governance of historical market data used as inputs in the key risk metric (eg Value at Risk, Economic Capital, Credit Counterparty Risk, Portfolio Stress Test).The core mandate of the team is split in three main groups:RtB operations, Governance and OptimizationKey responsibilities include procurement of historical market data, perform data quality checks and remediation where required, generation of market data (DB Analytics) objects, Exposure Info and Pricing Info objects for Historical Simulation Full Revaluation, production of key KPIs & governance, optimization of existing processes, face off to regulatory and audit engagements. Market Data AnalyticsKey responsibilities include development of proxy methodologies where historical data does not exist (including new risk factors introduced as a result of IBOR migration), development of approaches for enhanced data quality assessment, specify business requirements for FRTB from a market data perspective (including interplay of ES, NMRF & RTPL), develop analytics supporting gap filling in historical time series and forecasting trends Market Data StrategyKey responsibilities include driving discussions between FO, IT and MDSA to define the target market data strategy, both from an architectural and functional perspective, Streamline various market data tools/applications in strategic infrastructure and drive the build out of a central market data utility for multiple users/models, ensure data alignment between FO/GVG and Risk, search for synergies with GVG and FO to drive cost efficiencyWhat well offer you

100% reimbursement under childcare assistance benefit (gender neutral)

Sponsorship for Industry relevant certifications and education

Accident and Term life Insurance

Your key responsibilities

Creating, implementing and documenting quantitative risk models and enhancements for accurate market risk capture in risk models

Driving discussions and defining requirements with Strats, Risk Methodology and IT for generation of historical time-series for more exotic risk factors

Providing quantitative and qualitative justifications for modelling choices, assumptions made, data selection, reliability of model inputs such market data

Validating model choices by theoretical proof and support them with empirical evidence (e.g. statistical analysis of historical market data or back-testing)

Recalibration of model parameters which are used in the internal risk and capital models for market risk, in particular for Value-at-Risk models

Develop reports or analytical tools to facilitate robust testing process, including automation in order to drive down costs and improve process.

Business & Functional testing skillsability to write runbooks; Ability to present the results data and any variances clearly to Risk Managers

Ensuring production stability and responding to queries on timeseries from market risk managers

Your skills and experience

Engineering, Economics, Statistics or other numerate discipline with excellent project experience and grades in quantitative and numerical coursework

Excellent quantitative and analytical abilities as demonstrated by grades in mathematics/physics/statistics/engineering mathematics,

Knowledge of financial pricing models, risk models would be desirable

Good high level programming skills for ex. Matlab, Python and experience in numerical coding is good to have

Education | Certification (Recommended):

Engineering or bachelors degree in finance from an accredited college or university with excellent project experience and grades in quantitative and numerical coursework.

Certification in Financial Risk Management will be a plus.

Business Competencies:

Communication - Experienced

Industry Knowledge - Experienced

Risk Management Basic

Innovation Basic

Managing Complexity - Basic

Technical Competencies:

Risk Management Experienced

Financial Product Knowledge - Experienced

How well support you