Responsibilities

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As a Senior Quant Researcher, you will join the “Quantitative Investment Strategies (QIS) Team,” consisting of four quant researchers dedicated to feature engineering and developing systematic trading strategies. Your work will primarily involve bottom-up research, with some top-down research opportunities. You will create white papers to enhance RavenPack’s reputation as a thought leader in the alternative data industry and present trading strategies to quantitative analysts. You will independently work on practical use cases that demonstrate the value of RavenPack data. Additionally, your responsibilities will include:

Identifying, validating, and amplifying predictive signals within our data while discerning and filtering out irrelevant information.

Formulating systematic trading strategies spanning multiple asset classes with a major focus on equities, enriching security-selection capabilities with Alternative Data across different holding periods.

Offering data-driven insights, engaging in discussions about your research, and presenting trading strategies to leading quantitative researchers and portfolio managers in the field.

Effectivelymunicating intricate analytical concepts to management in a clear and concise manner.

What We're Looking For:

A PhD/MSc in Quantitative orputational Finance, or from any related fields including Machine Learning, Econometrics, Applied Mathematics, etc.

5+ years of relevant work experience as a quantitative researcher, manipulating large and noisy alternative datasets for features engineering, signal amplification, and portfolio backtesting.

Outstanding quantitative, analytical, and problem-solving skills, with proven ability to develop original research and hypothesis testing.

Demonstrated proficiency in at least Python and SQL.

Strong enthusiasm for technology, and familiarity with big data technologies coupled with proficiency in machine learning is highly advantageous.