We are looking to hire a talented individual to be part of a team surrounding the acquisition, cleaning and verification of financial reference and high frequency tick ata. Real world data is messy and requires preprocessing over and beyond just visually scanning data and updating bad records. It is critical to have good data as input to successful financial modeling. Typical problems include bad ticks in isolation or succession, missing data, bad dates, transposition errors, outliers, delayed data, dates on weekend or holidayor out of order, and incongruent sources.The complexity in cleaning the data lies in handling marginal errors whilst retaining the reality and statistical properties of the data.This is a challenging and rewarding opportunity for someone passionate about technology, extremely meticulous and detail orientated, with a drive for producing high quality working a hands-on role. Your primary goal shall be to improve the robustness and quality of the data that is made available for Research and Trading.

If you have excellent interpersonal, oral and written communication skills, and are a good team player then we want to hear from you, please contact us at: info@quantres.com, and be sure to clearly specify the position you are applying for.