One of the top performing Alpha generating quant research teams is looking to add a quant analyst to their team. The team is responsible for the research and design of quantitative investment strategies, which include but are not limited to, alpha generation through stock selection, portfolio construction, and quantitative analysis. The group have a keen interest in combining the worlds of data science and quant research and have successfully utilized unstructured datasets, Natural Language Processing (NLP) and machine learning techniques to generate stock-selection and macroeconomic signals. These signals are used in the design of long-short investment strategies. In addition to developing new signals you will also be tasked with improving existing signals and evaluating the impact of changes to methodology.
You should be an experienced quant researcher with a strong backgrounds in Computer Science and Statistics. This is a critical position with the potential to make immediate, significant impacts to the business through the development of alpha-generating quant signals.
Research responsibilities will include:
• Equity alpha signal research using machine learning techniques
• Alpha Factor Research through data selection and wrangling, prototyping regression models, and back testing to screen for new alpha signals using Python
• Quantitative research for equity long/short strategies through the analysis of market intelligence data and creation of stock selection signals
• Building automated tools to back-test strategies and analyze portfolio risk exposure
• Conducting data-driven equity research, statistics modeling, data mining, and time series analysis.
• Working on the launch of new equity products as a result of successful research.
• Working on alpha testing frameworks
The ideal candidate will have worked in a team which has built a stock selection alpha strategy from proprietary “big data”.
All applicants must be proficient in Python.
In order to apply please send your CV in WORD FORMAT to firstname.lastname@example.org or call 02080044001
Interviews have already begun to take place.