Big Data in Investment Research @ Canada Pension Plan Investment Board

May 27, 2019 · Toronto, Canada

In this iteration of the Toronto Women’s Data Group Meetup, three women focused on advancing CPPIB’s data-driven investment research framework join us to talk through the whole data-driven research lifecycle. From data exploration and sourcing to cleansing and integrating with existing models, engines and technology stack before finally delivering the output in a variety of forms – visualizations to forecasts - this session will cover all the stages of the lifecycle for both discretionary and systematic investment teams.

We welcome attendees from all industries to our session because we see parallels in the data-driven research lifecycles across industries – from clinical research to consumer insights – and will be laying out the basics of the data-driven research lifecycle before diving deeper into specific stages of the data and portfolio engineering process.

6:00pm to 6:30pm - Networking
6:30pm to 7:15 - Presentations
7:15 to 7:30pm - Q&A
7:30pm to 8:00pm - Networking

Fei Jia is a Senior Associate in the Data Engineering team under CPPIB’s Research and Innovation Group in the Capital Markets and Factor Investing Division. She joined the company in 2013 after finishing her Master’s studies in Mathematical Finance at University of Toronto. She focuses on exploring new, value-generating, orthogonal datasets, building data pipeline and infrastructure for the team’s quantitative investment research. Along with her work in data exploration and data management, she is also developing an alternative data road map to scale the testing, onboarding and integration of big data into the quantitative investing workflow at CPPIB. She holds a Bachelor of Mathematics degree from University of Waterloo.

Nikita Pillai is an Alternative Data Scout at CPPIB in the Technology & Data team. She is responsible for global data sourcing and strategy as it relates to unique, unstructured “alternative” data sets and their ability to drive alpha and refine fundamental and demand forecasting models. She joined CPPIB in April 2019 and prior to CPPIB was at global financial technology and data provider – FactSet Research Systems – where she was heading FactSet Canada’s Content & Technology Solutions team; developing alternative data partnerships with both vendors and clients on the buy-side. Nikita graduated from McGill University with a Bachelor’s degree in Economics and is currently pursuing her Masters in Finance from Queen’s University.

Roxanne Zalucky is a Portfolio Engineer for the Quantitative Strategies team in CPPIB’s Capital Markets group. The Portfolio Engineering team works with the business to build analytical tools needed for research as well as maintain a quantitative trading production environment. She joined the group in September 2017, after working at Two Sigma Investments, an NYC hedge fund, as a quant trader for the US equities portfolio. Zalucky holds a Bachelors of Arts in Economics from McGill University and a Masters in Computer Science from Stevens Institute of Technology in Hoboken, New Jersey.

Leyla Imanirad is a Senior Research Associate at Bristol Gate Capital Partners. Bristol Gate uses machine learning and other data science techniques in combination with fundamental analysis to construct high dividend growth portfolios. At Bristol Gate, Leyla initially led the data and technology acquisition efforts to build an appropriate research infrastructure. She further worked on the design & development of predictive models, as well as portfolio construction tools. Prior to that, Leyla worked at TD Bank in both software development and quantitative research roles. She has a Bachelor’s degree in Computer Engineering and a Master’s degree in Computer and Biomedical Engineering from the University of Toronto.

Event organizers
  • Toronto Women's Data Group

    This group is for women** interested in data science, data analytics, data engineering, and math and stats. The purpose is to provide an open and fun environment for women to network, learn and innovate. This group is open to women already in or aspiring to be in data driven fields. **This is an inclusive definition of “women” and we welcome trans, genderqueer, and non-binary folks who identify as female.

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