Quant Developer - Python, Machine Learning

Job Description:

A Quant Developer would be required to draw upon his/her computer science, mathematical and analytical abilities to build predictive models to improve trader performance in extremely competitive markets.

A Quant Developer would be expected to ensure the development of new models as well as improvement of the existing models and keep the team updated on the latest developments in the field of quantitative investment research.

Research at Algo One follows an assembly line approach, where the various stations are feature engineering, predictive modelling, strategy backtesting, risk management, etc.

a) Feature Engineering: Continuously identify new sources of alpha, identify predictive power, handle correlation, combine features. All this on extremely large datasets.

b) Predictive Modelling: On-going iterations of linear and non-linear models, higher-level ensembles, taking logical steps from one model to another in the vast jungle of advancements, building the infrastructure to support such exploration.

c) Strategy Backtesting: Analysing various ways to express a trade idea, understand market microstructure, trading costs, etc. Building realistic backtests is the key.

d) Risk Management: Detailed understanding of the various risks, return drivers for the strategy, sectoral/temporal concentrations, trade sizing, allocation rules within a broader portfolio

Typically, a Quant Developer would be in charge of handling multiple responsibilities either directly or by managing teams. We encourage individuals to take on different roles in various project cycles, to give them a flavor of the entire lifecycle.

Skills Required:

- Strong background in machine learning based predictive modeling.
- Strong quantitative skills.
- Exceptional analytical and problem solving skills.
- Excellent coding skills (Python/R/Java/C/C++).
- Willingness and ability to learn and take up varied responsibilities over time.
- A genuine interest in financial markets.
- Good communication skills, comfortable with explaining complicated models to a wide audience.
- A team player. Ability to brainstorm and enhance the learning experience.
- Doesn't give up, has patience to get it right, never makes the same mistake twice.