Quantitative Research Associate
1 month ago
Overview
SIG is a sophisticated and influential trading firm, active on the world’s major securities and derivatives exchanges. Our European headquarters is based in Dublin, where we employ over 450 people in Trading, Quantitative Research & Technology across a range of trading strategies, including Exchange Traded Funds, Commodities, Options, Fixed Income, Equity Derivatives and Convertible Bonds.
Nellie Analytics – an affiliate of SIG – is focused on geo-political and sports analytics. Due to our continued growth, we are continually looking for someone with an understanding and interest in sports analytics to join our Quantitative Research team. Quantitative Researchers at SIG use research to better understand markets and to identify, develop and improve strategies for the firm. This is an exciting opportunity to be part of an early-stage initiative and be an influencer to help shape new product development as the business opportunity evolves.
This is a research, development, and modelling role in which you will use your background in mathematics and statistics to seek out reliable, timely sports data to clean, analyse, and transform into algorithms and strategies. This position will likely require intermittent international travel.
Tasks will include:
Building probabilistic models for Sports Understanding, refining, and maintaining our current strategies Working closely with fellow traders, quants, and developers to improve our mathematical models and software Analysing past trades and historical data in a constant search for improvementWhat we're looking for
A PhD/Masters with significant research experience in a numerate or technical discipline such as Mathematics, Stats, CS, Physics, Economics etc. Exceptional quantitative and statistical understanding Very strong attention to detail. Interest in sports data/analytics with an understanding of some subset of--NFL, NBA, MLB, NHL, Soccer or Tennis Data mining and modelling experience Practical programming experience Ability to excel in a fast-paced environment Strong interpersonal and English communication skills Attentiveness and ability to react to changing priorities and manage multiple tasks simultaneously is essential Knowledge of data manipulation libraries such as Pandas/Numpy Experience building models with framework such as STAN/Scikit/Statsmodels/TF/Keras is a plus
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