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CIB QR Quantitative Research Equity Finance VP

11.00 to 12.00 Years   Mumbai City   20 May, 2019
JPMorgan
Job LocationMumbai City
EducationNot Mentioned
SalaryNot Disclosed
Industryanking / Financial Services
Functional AreaFinance / Accounts / Tax
EmploymentTypeFull-time

Job Description

JPMorgan Investor Services (IS) Quantitative Research team is looking for a strong quant to support all quantitative aspects of the Delta 1, Equity Finance and Global Clearing businesses.The IS team main activities involve:

  1. Risk & Pricing: Use probabilities, stochastic processes & other math to model financial instruments & risks.Given the nature of the business typical risks and payoffs modelled present non-linearities in the rates, borrow and dividend space but are typically of delta1 nature (linear in the spot).Models span across single name and portfolio level.
  2. Data Analytics: Analyze data from markets, transactions and business processes, to provide insights into prices and risks, and aid decision making and optimizations.This is accomplished through a combination of Statistics and Machine Learning techniques.
  3. Trading and Business Optimizations: Determining optimal strategies for interacting with the markets to finance or hedge the book This entails modelling synergies between different areas, liquidity, balance sheet, as well as linear and non-linear constraints. This is delivered though platforms or algos that fully automate or augment business functions.The primary responsibilities for this role will include:
  • Lead forward developments on trading optimization platforms employed by the Equity Finance business to manage SBL, Synthetic and Cash trading activities.
  • Put in place large and scalable architectures, linearize state-space to deal with massive data sets, vectorised coding and distributed computing.
  • Liaise with multiple stake-holders to formulate a multi-dimensional objective function across metrics: PnL, Liquidity, RWA, ROA, etc.
  • Model trading book dynamics, transaction costs potentially employing Statistical and Machine Learning techniques.
  • Document and test new/existing models with traders and with other various control groups, such as the Model Review Group
  • Implementation of models in C++ and Python proprietary libraries.
  • Excellent Math background.
  • Ability to work with big-data and experience in formulation of optimizations.
  • Strong experience in linearization of state-space.
  • Strong analytical and problem solving abilities.
  • Strong communication/presentation skills.
  • Strong programming skills (C++, Python).
  • Experience with parallel computing, vectorization and memory management is positively regarded.
  • Solid knowledge with CPLEX, GUROBI, MOSEK or other main stream optimization packages is desirable.
  • Knowledge of Financial Engineering, Secured Financing and Prime is a plus.
  • Previous experience with formulation of Statistical models / hands-on implementation of Machine Learning neural networks is a plus.
  • Advanced degree in a technical field from a top-tier school/program: engineering, sciences, computer science, applied math.
Ideal candidates for these positions would be a graduate/post-graduate from a premier college or institute. A computer science or mathematics background will be most suitable. ,

Keyskills :
financialservicesmanagementquantitativeresearchjavaj2eedataanalyticsmanualtestingqlplsql

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