Our client is a global investment management firm that employs a diversified range of systematic and quantitative strategies aross financial markets, with the objective of delivering high-quality, uncorrelated returns for clients.
They attribute their success to rigorous scientific reseach and possess deep expertise in trading, technology, and operations. As a technology and data driven firm, they design and build their own cutting-edge sustems, ranging from high performance trading platforms to large scale data analysis and compute farms. With offices around the globe, they emphasize true global collaboration by functionally aligning their investment, technology, and operations teams worldwide.
Position Overview
Maintain and upgrade the strategies' codebase and configurations within the firm's automated trading framework.
Handle and manage large datasets used in both research and production environments.
Conduct monitoring of trading activities, both live and historical, including post-trade analysis and production reconciliation.
Qualifications
Education: Bachelor's degree in a quantitative or related field (includes degrees in Mathematics, Statistics, Econometrics, Financial Engineering, Operations Research, Computer Science and Physics); advanced degree preferred.
Years Experience Guidelines
Graduate level up to 2 years of relevant experience.
Required Skillset
Shows a keen interest in Quantitative Finance.
Applies a quantitative approach to problem-solving and decision-making.
Thrives in fast-paced environments with a strong sense of urgency and proactive mindset.
Proficinecy in Python, C++, or Java.
Communicates effectively with global teammates to drive alignment and results.
Demonstrates strong collaboration skills with trading, analyst, and quantiative teams.
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