Quantitative Research Consultant
Analytics team is building up alternative data platform to detect signals which can potentially position our investment process ahead of the market and enhance our returns. We are currently looking for a candidate who will apply machine learning techniques, particularly natural language processing, to textual documents including public company’s 10-K filings, press releases, analyst call transcripts, etc. The focus is to preprocess the documents, transform the documents to quantitative metrics that are potentially correlated with future investment results. This effort will involve extensive collaboration with the firm’s quantitative researchers in the corporate credit and equity areas.
1) Minimum bachelor degree in science and engineering with math and statistics background. Top school graduates are preferred.
2) 5-7 years of working experience in Python. Knowledge of nltk, sklearn, gensim, and spacy are preferred.
3) 3-5 years of extensive data processing experience. Strong attention to detail and willingness to get hands dirty in checking and cleaning data quality.
4) Ability to read research papers and quickly write up own code to verify the claims in the papers.
5) Disciplined and well organized. This project is part of long term initiatives in the firm. Candidates need to document the code and automate the processes at each step along the pipeline.