- Type
- Full-time
- Department
- Education
- Education
- PhD
Description
Your role
- 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
Your expertise
- 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.
Preferred
- 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
Skills
PythonSQLMachine LearningR