Quant Developer

26 سبتمبر، 2022

0 2 2 دقائق

Quant Developer

الوصف الوظيفي

Job Description

Our client is a well-established international FX broker and online trading platform. As part of their growth, we are recruiting an experienced Python based Quant risk developer from the financial services sector such as a bank, asset management, currency or FX trading, CFDs, equities or crypto currency.
The role is responsible for the development and maintenance of the market data risk analytics applications and infrastructure and all Quant-related initiatives.
Candidates must have 3+ years’ experience in Python programming language and application design for derivative and risk management models.
Role Summary

Build a Python risk analytics library from scratch covering risk exposure, trading activity, P&L performance, Value at Risk, scenario analysis and stress testing.
Implement Python script to manipulate data structure, format and price the financial instrument using both self-created library embedded and/or pre-defined library.
Continuously improve the risk data model and build risk data marts and analytic pricing models.
Liaise with IT to ensure risk analytics are properly documented and integrated across the entire Tech infrastructure.
Collaborate with the Dealing team to optimize the portfolio risk quantification continuously and visualization.
Work with real time high frequency and time series data including static referenced and fundamental data.
Build, maintain, and improve real time monitoring applications for internal trading activity and public blockchain data.

Mandatory Skills & Experience

3+ years as a Python Quant trading developer with a strong understanding of Object-oriented programming (OOP), Quandl API and Pandas, NumPy, PySpark and time series in FX, crypto currencies, derivatives, equities, commodities, foreign exchange, FOREX, stock exchange, derivative instruments and financial instruments.
Strong knowledge of OOP, data structures and algorithms and Linux shell scripts.
Data Analysis – sound understanding of data modelling (EER concepts, normalization, etc).
Good understanding of core statistical concepts such as distributions, correlations and regressions.
Good understanding of trading workflow and portfolio concepts such as orders, margin, P&L and exposure.
Broad understanding of financial & quantitative models, fixed income products and interest rate curves in both developed and emerging markets
Familiarity with Refinitiv quantitative pricing service API is an advantage.
Good understanding of VaR and scenario analysis.
C++ and Python, JavaScript and Perl programming and R statistical language experience.
SQL – ability to write complex queries, stored procedures.
Productionization models using GIT/SDLC/other version control tools.
Data Visualization with any popular BI tool.
Machine Learning techniques.