Combine quantitative processes with fundamental insights to identify industry key performance indicators, develop sector-specific signals, track company specific risks etc.
Develop, back test, and implement statistical models to test the efficacy of alternative data to gain insights into and forecast future company performance using alternative data.
Build tools to query, clean, analyze raw data through databases, and work closely with data and technology team to ensure data quality and delivery
Actively source new ideas and collaborate with other research teams; providing statistical measures to both internal and external clients

Advanced degree in quantitative field such as statistics, engineering, mathematics or finance, PhD preferred
5-10 years’ experience in statistics/AI and time series modeling, proficiency working with large dataset, machine learning, data mining, and numerical methods
Experience leading a team of data scientists
Conducting statistical analysis and building time series models including VAR, DLM, state space models etc
Utilizing machine learning models like gradient boosting, random forest, k-means clustering and other statistical techniques.
Programming using Python, R, SQL.
Experience with cloud ML is a plus.

Knowledge of natural language processing, including techniques such as Naive Bayes, Latent Dirichlet allocation and extractive text summarization;
Fundamental financial (equity or fixed income) research experience is a plus
Creative thinking and problem-solving skills; able to decompose complex problems into manageable pieces
Strong verbal and written communication skills; able to present quantitative solutions clearly to both internal and external clients
Team oriented; able to collaborate with a range of functional teams and resolve conflicts as necessary

Data Scientist

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