Senior Associate - Trading - Investment Bank

Looking for a candidate well versed in either algorithm trading i.e someone supporting trade and well versed in Algorithm or someone who is supporting trade and is well versed in asset classes like equity,derivatives, FX, bonds. Also the person should have technical knowledge in Java/C++/C/Phython/ etc

Location-Mumbai

Experience- 2-7 yrs

Job responsibilities:

The work covers a number of product lines including pre-trade, intra-trade, post-trade products and electronic execution platforms across all major global markets.

A successful candidate will have a demonstrated ability in building pre-trade, intra-trade, and post- trade analytics tools and a working knowledge of equites market microstructure (or other asset class). The candidate will use their knowledge of statistics to design, implement and validate models. They will use their strong programming capability to collect, manipulate and aggregate large data sets and develop production ready components. They will use their presentation skills to summarise model outcomes and write up compelling analytical notes for internal desks and external clients.

Data types that the team works with include ultra-high frequency market trade and quote (TAQ) data and electronic trading order and execution data. This data is used to develop

- Algorithmic trading analytics

- Microstructure research

- Pre-trade cost and risk estimates

- Quantitative research for internal and external publications

- Transaction Cost Analysis (TCA) and improvement of strategy performance

- Bespoke quantitative research for EE clients

The employee will be responsible for the accuracy and completeness of all modelling and analysis.

Education:Bachelor's degree in Computer Science/Electrical Engineering/Mathematics/Statistics from a premier academic institution.

Skills:

- Strong programming and computer science skills. Advanced knowledge of C++ or Java (any one) along with Excel/VBA and Microsoft Office. Prior experience of functional programming (e.g. q/kdb+) and R is an added advantage.

- Strong mathematical background, with good knowledge in one or more of the following disciplines - probability, quantitative finance, computer science, linear algebra, numerical methods, statistics, econometrics, time series analysis

- Good communication and presentation skills

- Ability to work under pressure, with minimal supervision, and in a team environment.

- Detail-oriented and with strong organisational skills