As a member of our Core Quant Trading Team, you are being hired with the mandate to expand our core trading activities in terms of strategies and markets.
You will be working in a highly collaborative environment and are expected to evolve into the role of a Desk-Head (for a particular market / strategy which you shall be managing end to end)
You will be working with our experienced traders, and are expected to be an intrinsic member of our core trading operations.
You will be supported by various non-trading support teams and our existing Quant Platform.
This is a front end trading role in a collaborative environment which demands a strong motivation to succeed
You will be undertaking quantitatively driven projects, hence would have to continuously learn new ML/Statistical/Analytical skills to successfully undertake these analytical projects.
Your Responsibilities Shall Include
Carrying out quantitative research with the view of building new predictors, modelling techniques and trading strategies. All of our effort needs to be quantitatively inclined and measurable
Expanding our current set of trading ideas into new markets and portfolios as we increase our market footprint.
Experimenting with our current set of trading ideas to improve them.
Work collaboratively within the core group and help in further development of the Quant Platform.
Adapt trading ideas and strategies to evolving market conditions over time.
Taking a leadership role to drive new Quant trading ideas, once you grow in the core team
Technical Background And Requirements
We believe that a lot of learning will happen on the job itself and therefore the most important requirement is having a high motivation to learn, seek continuous feedback and improve based upon it
High level of proficiency in an Analysis framework preferably python
Strong Quantitative abilities
A keen interest in the functioning of financial markets and data science
An analytical and problem solving mind-set with a strong attention to detail
Preferable
Knowledge of C++
Knowledge of Statistical Modelling, Machine Learning Algorithms and Techniques
