S Posted byRecruiterQuantitative Data Software Engineer based in our European HQ in Dublin, Ireland
Founded in 1987, SIG has grown from an options trading firm on the Philadelphia Stock Exchange to one of the world’s largest privately held financial institutions. Today, with offices around the world, we trade almost every major financial product, and we are recognized for our disciplined and quantitative trading approach, and our leading-edge trading systems. We established our European headquarters in Dublin over 20 years ago and now employ over 550 people here in Trading, Technology, Research, Operations,pliance, Legal, Finance, and HR.
Technology is core to the success of our business. We have more than 800 technologists building our systems from the ground up. We are on the leading edge of low-latency and high performance trading and our technology drives every aspect of our business. Our developers and engineers work together to build solutions using the newest and fastest technology available. We work in aplex, distributed environment where we continually strive to improve systems capacity, increase speed, ensure stability and mitigate risk in every system
As a Quantitative Data Software Engineer you will be working together with the quantitative research and trading teams, as well as with the trading strategy developers to: - source and cleanse data, develop and maintain data pipelines as required by quant research and trading - assist with researching new trading opportunities; - develop, maintain and deploy interactive and packaged reports that will directly influence trading strategies - performance-tune existing applications and processes, improve existing codebases and data flows to allow for efficient processing of large data sets
What we’re looking for:
1. PhD, Masters in a technical discipline
2. Experience with the Python data science stack: NumPy, pandas etc.
3. Experience with numeric data storage methodologies, hdf5
4. Experience with processing of large and varied data sets
5. Experience of working in a Linux environment
6. Ability to understand mathematical algorithms and develop high-performance implementations
7. Strong interpersonal andmunication skills for interacting with traders, quantitative analysts, and other software developers
8. Experience or interest in areas such as capital markets, probability, game theory and the application of IT solutions to these areas is a plus