A leading global investment and technology development firm based in New York, is actively seeking talented individuals to join its Futures team in a quantitative analyst capacity. This team employs mathematical techniques and software development to create, analyse, and implement statistical models for computerized financial trading strategies.
As a quantitative analyst, you will be tasked with developing and maintaining machine learning models for the firm's trading strategies. Responsibilities include analysing and developing computer-based quantitative models for pricing securities, optimizing execution strategies, managing portfolios, and controlling risk. You'll work on improving current models and trading systems by developing infrastructure and analytical software in various computer languages. Additionally, you will build models to identify pricing anomalies in liquidly traded currencies, futures instruments, and other key macroeconomic instruments.
Your role will involve analysing the economic and behavioural drivers of pricing, developing strategies to forecast pricing anomalies, and building quantitative models to test and validate hypotheses. Rigorous testing and documentation of models' performance will be a key aspect of your responsibilities. You may also contribute to writing production code for strategies within the systematic trading infrastructure.
Further tasks include developing models for understanding transaction costs, optimizing execution strategies, managing portfolios, and controlling risk. Your work will contribute to the improvement of toolsets, Python libraries for quantitative modelling, and the analysis of pricing anomalies. Evaluating runtime efficiency of models and implementing optimizations, analysing discretionary trading ideas, and transforming them into systematic forecasts will be part of your day-to-day activities.
Candidates must hold a Doctor of Philosophy degree in computer science, mathematics, physics, or a related field of study. Successful candidates will have knowledge and experience acquired through academic research and/or coursework, demonstrating expertise in scientific research methods, theory of modern machine learning and deep learning, frameworks for deep learning, programming and quantitative modelling, probability theory and statistics, and statistical tests for interpreting empirical results.
The annual base salary for this position is highly competitive and includes an annual bonus and generous benefits. If you are a highly qualified individual seeking to contribute your expertise to innovative financial strategies, please contact or send your CV to Deepthi Kapavarapu at deepthi.kapavarapu@ap-technical.com
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