At Rivermap, we hire talented people and give them autonomy as well as support to build innovative technology solution and product. As a research analyst, you are responsible for performing research in the area of data science and investment science. If you are looking for a career opportunity where you can make impactful contribution that transforms the way people use data and technology in financial world, we would love to invite you to join our team. We are an incubatee of the Cyberport Incubation Program. Our clients include reputable financial institutions in Hong Kong and China.
Responsibilities
Machine Learning Research: Perform machine learning research to develop innovative models and algorithms for stock return forecasts, leveraging advanced techniques to enhance investment strategies and decision-making processes.
NLP Application: Conduct NLP research focusing on thematic investing and sentiment analysis, utilizing cutting-edge techniques to classify stocks and extract valuable sentiment information from diverse sources such as financial documents and social media data, providing valuable insights for informed investment decisions.
Portfolio Management: Engage in research activities related to portfolio optimization and risk forecasting, employing mathematical modeling and statistical analysis to develop robust strategies for managing investment portfolios and effectively forecasting potential risks, contributing to the optimization of investment strategies.
Database Management: Develop and manage databases and applications that store and process extensive financial and market data, ensuring data quality, integrity, and efficient retrieval, collaborating with the data team to design and implement scalable and reliable systems supporting research requirements.
Academic Research: Contribute to academic journal publications by collaborating with researchers, analyzing experimental results, and sharing innovative findings to advance the fields of machine learning, indexing and quant investment.
What we look for
Strong problem solving skills with an emphasis on research and product development
Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks) and their real-world applications
Strong interest in Natural Language Processing (NLP)
Knowledge of statistical techniques and concepts (regression, time series analysis, statistical tests.) and experience with applications
Strong programming skills, including C#, Python, Matlab
Strong database knowledge (SQL) to help developing data storage and retrieval tools
Enthusiasm about working in a startup environment
Graduate in numerate discipline including Engineering, Computer Science, Mathematics, Statistics, Physics
