Job Information
Wolfe Research Director in New York, New York
Lead quantitative research efforts including data scouting, research writing, product development, and client marketing. Manage a team of quantitative researchers including the research pipeline and product development cycle. Perform data scouting, source novel datasets including options data, alternative data, NLP data sources, and other specialized datasets. Manage data vendor relationships including price negotiations and scope analysis. Through understanding and development of the following machine learning models: deep learning, NLP Large Language Model, Transformer Neural Networks, Gradient Boosted Trees, Convolution Neural Networks, and Bayesian Machine Learning. Products should be designed around these Machine Learning Models. Through understanding and development of the following NLP Models: BERT, XLNet, RoBERTa, ALBERT, PaLM, GPT-3. Products should be designed around these NLP Models. Perform research, write academic style research reports, and publish research reports on stock selection algorithms, machine learning, NLP models, risk & portfolio construction, optimization, and risk model design. Develop Dashboards, APIs, and User Interfaces used external facing clients to analyze textual data using NLP models. Spearhead, lead and designs data and investable strategy product components that clients utilize to make intelligent and systematic investment decisions. Consider transaction cost, shorting cost, leverage, data needs, liquidity, tradability, market microstructure when design both data and investable product. Market and present all our investable strategies and data products to clients, sales teams, and investors. Travel within the US, Europe and Asia to present our products to clients. Develop strategic partnerships for research and product distribution. Manage partner relationships.Master’s Degree in Financial Engineering, Mathematical Finance, Operation Research, Computer Science, Machine Learning or related fields with 3 years’ experience in statistical modeling and computer programming. Experience must include 3 years’ with: (1) equity and multi-asset multifactor models; (2) Computer programming in R, Python, and C++; (3) designing stock selection models; (4) advanced machine learning techniques; (5) mathematical optimization with dimensionality; (6) portfolio construction techniques (e.g., mean-variance, heuristic, Black-Litterman, risk parity, maximum diversification); (7) expert NLP modelling skills; (8) global macro risk model design; (9) databases and dataset construction; (10) behavioral finance, asset pricing theory, financial econometrics, and global macroeconomics; and (11) Computational statistics. Less than 5% travel.
Minimum Salary: 278000 Maximum Salary: 285000 Salary Unit: Yearly