Quantitative Research - Credit EMM Modeler - VP
Mumbai, India | Global Securities, Investment and Retail Banking Firm
Functions:Financial Services Professional
Job Description:51 people have viewed this job
Research, development, back-testing and reporting of market-making and quoting strategies
Applying machine learning and statistical techniques to analyze market moves and trade data
Development, deployment and support of production code for automated and semi-automated quoting and trading of SPG products in our in-house system, Athena
Working with the Trading Desk to ensure optimal usage of automated strategies and analytical tools, as well as to identify and develop business intelligence tools
Working with Technology on ongoing improvements to market-making infrastructure, as well as on sourcing, maintaining and exposing various market and reference data feeds
Working with the Model Review Group to ensure models pass strict in-house standards
We work in a very dynamic environment, and excellent communication skills are required in our interaction with trading, technology, and control functions. A healthy interest in good software design principles is essential. The role requires a detailed understanding of the SPG TBA market. It is understood that the candidate may not have this knowledge from previous experience, but the successful candidate would be highly motivated to gain this knowledge. A Ph.D. in a numerate subject, specifically focusing on Deep Learning, Reinforcement Learning or Statistical/Probabilistic Modeling, from a top academic institution is highly desirable, but not an absolute requirement
Very strong Stochastic Modeling and Data Science background, including Statistics, Probability, Machine Learning and Deep Learning
Excellent practical data-analysis skills on real datasets, including familiarity with methods for working with large data and tools for data analysis, e.g., Pandas, Numpy, Scikit-learn, TensorFlow, Keras, etc.
Familiarity with Time-Series analysis using Deep Learning, as well as experience in Reinforcement Learning would be a plus
Object Oriented Programming (OOP) and software design skills, preferably obtained using C++. Extensive Python experience would be a plus as would be experience with Reactive Programming
Attention to detail: thorough and persistent in delivering production quality analytics
Excellent communication skills; explains her/his thought process clearly and communicates model and strategy behaviors to a non-technical audience efficiently
Ability to work in a high-pressure environment
Pro-active attitude. Should have a natural interest to learn about our business, models, and infrastructure.
Parallel/distributed computing experience a plus.
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.