Brodie applies machine learning, statistics and quantitative methods in financial derivatives pricing to forecast and price residential real estate derivatives. In addition, he manages the quantitative research and portfolio optimization strategy, leveraging mass property level transaction databases and large-scale parallel processing clusters. Prior to Unison, Brodie worked as a Quantitative Strategist for the Financial Institutions Group at Goldman Sachs in New York City.
Brodie received his Master of Financial Engineering (MFE) and Bachelor of Science in Engineering Physics from UC Berkeley. He lectures a summer course on Quantitative Methods in Derivatives Pricing and a Machine Learning workshop at UC Berkeley for students in the MFE program.
Winfield employs advanced quantitative finance knowledge and data science skills in investment research and portfolio management. His role involves option valuation, risk modeling, and portfolio optimization activities. He provides analytical firepower, leads research projects and develops next-generation technology to support the investment decision-making process. Before joining Unison, Winfield worked on portfolio analytics and execution research at FORT L.P., a quantitative hedge fund based in Washington, D.C. Prior to that, he worked at Micron Technology where he led global process optimization projects by leveraging and analyzing mass production data using statistical and machine learning techniques.
Winfield received a Bachelor of Engineering with First Class Honors from Nanyang Technological University, Singapore and a Master of Financial Engineering from the Haas School of Business, UC Berkeley.
Aditya assists the research team by handling data structuring, cleaning, and data science tasks for building quantitative models. In addition, he also helps in developing prudent strategies for data acquisition and statistical methods in order to build reliable forecasting models for accurate predictions.
Previously, Aditya worked as a data analyst with Ecolibrium Energy, helping companies in various industry verticals to intelligently manage their electrical assets and energy usage. While at Ecolibrium, Aditya developed two patent-pending methods for online conditional monitoring of electrical machines in real-time using predictive maintenance algorithms. Aditya holds a Master's degree in Business Analytics from the University of Illinois at Chicago and a Bachelor's degree in Information and Communication Technology from Dhirubhai Ambani Institute of Information and Communication Technology in Gandhinagar, Gujarat, India.
Scott utilizes knowledge in quantitative finance, statistical modeling and machine learning to price financial derivatives and predict default risk. In addition, he leads the effort to develop new technology to increase efficiency in underwriting and investment management operation and build automatic reporting to support business decisions. Prior to Unison, Scott worked as a quantitative analyst at a trust in Beijing where he helped build statistical models and data science modesl to optimize performance of a multi-asset fund. Scott received his Master of Science in Financial Engineering from University of Illinois at Urbana Champaign and Bachelor of Business Administration from Hunan University in China.
A scientist by day and an artist by night, Wenyao is an enthusiast of data visualization, solving mathematical puzzles and occasionally, building Lego sets. At Unison, he derives insights from data using a variety of statistical tools and adds value through standardization and automation. Prior to that, he worked as a credit risk analyst at a commercial bank. Wenyao received a Master of Financial Engineering from UCLA Anderson School of Management and a Bachelor of Science from Shanghai Jiao Tong University.