Quantitative Researcher - Modeller at Information Management Consultants, Inc.

Sydney, New South Wales, Australia -

Full Time

Start Date

Immediate

Expiry Date

20 May, 26

Salary

0.0

Posted On

19 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Deep Learning, Prediction Quality, Feature Engineering, Sampling, Hyperparameters, Network Architecture, Distributed Computing, Machine Learning, Delta One Trading, Model Development, Data Analysis, TensorFlow, PyTorch, CNN, RNN, LSTM

Industry

Financial Services

Description

IMC is looking for experienced quant researchers to develop high to mid frequency delta one trading strategies and predictive models for the APAC markets. If you’re excited about helping to push the boundaries of what we can do with Machine Learning in trading, unlocking the significant edges we have in execution, and collaborating to become the best trading firm worldwide, this may be the role for you. You will be responsible for performing large scale data analysis to derive statistically profitable predictions of market behaviour. These predictions are used to inform all of our trading, and improvements have a high and visible impact across the office. You will also help to shape the direction we take across research and tooling. We have longstanding and significant edges across market access, global reach, Options understanding and low latency. The rapid growth we’ve already seen in Machine Learning has unlocked these edges, and some of the most interesting and impactful problems are now being tackled. You will work as part of an established and growing research team, collaborating closely with traders, software and hardware developers to find improvements to our models and see them impact our production results. IMC competes and wins as a team, with open idea sharing and collaboration across disciplines, desks and offices. Your Core Responsibilities: Leverage deep learning techniques to improve prediction quality in a trading context Collaborate with feature engineers and traders, to help ensure the feature set is crafted and used to maximum effect Develop and improve sampling, weighting, cost, target, hyperparameters and network architecture to suit a range of problems and data presentations Push the team forward, by keeping abreast of the latest developments in industry and academia, and tackling some of the hardest problems we have in the quant space Mentor and grow the skills of more junior colleagues in the space, and clearly and simply explain complex concepts Apply understanding of distributed computing, and how to align training hardware and approach to rapidly achieve strong results on very large datasets Your Skills and Experience: Graduate & Postgraduate study from top universities, majoring in machine learning, statistics, or STEM subjects 3+ years experience as a quantitative modeller, with specific experience in the high to mid frequency delta one space. Have a proven track record of developing and improving deep learning models with proven outperformance in production Strong programming experience in at least one language, and mainstream deep learning framework (TensorFlow, PyTorch or other) Deep understanding of the strengths & weaknesses of CNN, RNN, LSTM and transformers About Us IMC is a global trading firm powered by a cutting-edge research environment and a world-class technology backbone. Since 1989, we’ve been a stabilizing force in financial markets, providing essential liquidity upon which market participants depend. Across our offices in the US, Europe, Asia Pacific, and India, our talented quant researchers, engineers, traders, and business operations professionals are united by our uniquely collaborative, high-performance culture, and our commitment to giving back. From entering dynamic new markets to embracing disruptive technologies, and from developing an innovative research environment to diversifying our trading strategies, we dare to continuously innovate and collaborate to succeed.

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Responsibilities

The role involves leveraging deep learning techniques to enhance prediction quality in trading contexts, collaborating with engineers and traders on feature sets, and developing/improving various model components like sampling and architecture. Responsibilities also include pushing research forward, mentoring junior colleagues, and applying distributed computing knowledge for large dataset processing.