Olga Kane is a Managing Director at Synthesis, a quantitative investment company, focusing on statistical arbitrage in equity markets. In her role, Olga oversees company's trading operations, data strategy, vendor management, and strategic partnerships. Prior to joining Synthesis, Olga was Head of Data Sourcing and Strategy at QST Financial, a proprietary algorithmic trading group, where she was responsible for managing the full cycle of data acquisition for investment research.
Olga joined QST Financial from ITI Group where she has spearheaded the launch of a multi-manager hedge fund platform focusing on quantitative investment strategies. Before that, she held a variety of senior roles in the alternative investments industry including Head of Operations and Investor Relations at Da Vinci Capital. She started her career as a client relations manager at Renaissance Capital. With over sixteen years of hands-on industry experience, she developed her professional expertise on the intersection of fundamental investment research and cutting-edge technologies transforming the industry.
Olga holds Master’s Degree in finance, MBA degree from Baruch College Zicklin School of Business and Chartered Alternative Investment Analyst (CAIA) designation. She passed FINRA exams: SEI, Series 65, Series 66. Olga recently completed Harvard Business School’s Executive Program for Leadership Development and Investment Management Workshop by Harvard Business School and CFA Institute.
A frequent speaker at industry conferences on topics of fintech, machine learning, data-driven investment research and data monetization, Olga is also a member of global advisory board of Quant Summit by Risk.net. Her previous conference speaking engagements include: AI and Data Science in Trading, Quant Strats, AI in Finance, The Trading Show, Quant Summit USA, Trade Tech Europe, Equities Leaders Summit, New York Alternative Investment Roundtable and many more. She was also a guest speaker at Artificial Intelligence in Finance Bootcamp and a guest lecturer at NYU graduate course on big data in finance.