Our client is a well-established international FX broker and online trading platform. As part of their growth, we are recruiting an experienced Python Risk or Quant 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.
Role Summary
Build a Python risk analytics library from scratch in Python 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.
Liaise with IT to ensure risk analytics are properly documented and integrated across the entire Tech infrastructure.
Collaborate with the Dealing team to continuously optimize the portfolio risk quantification and visualization.
Work with real time high frequency and time series data including static referenced and fundamental 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.
JavaScript
SQL – ability to write complex queries, stored procedures.
Data Analysis - sound understanding of data modelling (EER concepts, normalization, etc)
Cloud solutions and platforms - Azure is an advantage
Data Visualization with any popular BI tool
Familiar with ORM
Machine Learning techniques
API development
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.
Good understanding of VaR and scenario analysis
Ability to make recommendations for system improvements.
Ability to handle large volumes of structured and unstructured data.
Familiarity with Refinitiv quantitative pricing service API is an advantage.
Education
MSc or BSc in Computer Science or scientific subject - preferably Maths, Physics or quantitative finance.
Candidate Profile
Currently living in United Arab Emirates.
Fluent in English.
Intellectually superior with the ability to challenge and validate results.
Excellent interpersonal, communication and presentation skills.