Tibra Capital - Quant Trader Winter Internship (4 weeks)

Job Description

• This 4 week Internship is based in Austinmer, NSW 
• Flexible dates to suit your University winter break
• Basic to intermediate level programming skills in either Python or C++ mandatory 
• Competitive remuneration & attractive benefits on offer 
• Candidates who have completed a full application will be contacted - this must include Resume (include expected University graduation dates), University academic transcript including current WAM/GPA (can be noted on resume), residency status (can be noted on resume) 

About the Role:

This role presents an excellent opportunity for penultimate or final year students to get exposure to real world derivative pricing and quantitative finance methods. You will assist in performing cutting edge research on the most competitive markets, designing and analysing algorithms, exploring financial markets structure, and contributing to the continual evolution of our quantitative trading strategies. Your coding skills will be key in building and maintaining the tools necessary for us to be successful.

Key Responsibilities:

• Assist in the evolution and implementation of the firms trading strategies
• Analysis of large volumes of real-world financial and price information
• Development and Optimization of algorithms
• Debugging and maintaining our code base

Knowledge & Skills Required:

• Studying towards a degree in Engineering, Computer Science, Software Engineering, Mathematics, Finance, Data Science or similar
• Programming experience (C++, Python, Java, C#, C or similar)
• Basic knowledge of options pricing theory, quantitative models and probability theory
• Be a reliable quick thinker who can work under pressure
• Solid written and verbal communication skills
• Team player but can work independently and unsupervised
• An excellent problem solver who can contribute innovative ideas

Advantages:

• Excellent programming skills
• Experience with numerical solution techniques, basic signal processing, machine learning or stochastic processes

Your Application must include:

• Resume (include expected University graduation dates)
• University academic transcript including current WAM/GPA (can be noted on resume)
• Residency status (can be noted on resume) 

Applications close: Friday 10th May AEST time