Panel Discussion (UTSG) - Everything You Want to Know About Data Science/Da...

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University of Toronto - St. George Campus

27 King's College Circle, GB120

Toronto, ON M5S 3H7


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Data Scientist is considered as one of the sexiest jobs in the 21st century. While the demand for data science talents keeps surging in Canada, the requirements from hiring companies are also very high. As a data science professional, one is expected to understand math, computer programming, machine learning, data visualization, as well as business domain knowledge. That’s why in the current Canadian job market, there’s a big talent gap.

WeCloudData invited over 5 data scientists and business analysts coming to the universities to talk about the trends in data science job market and share their personal stories on how they landed their dream jobs in the data science field.

Tell us what you want to know about data scientist jobs and data analyst jobs.

You are the one who decide the topics of this panel discussion!


Jonathan Wang, CFA, Senior Consultant, BMO

Jonathan has over 15 years of experience in Canadian banking industry. He is a seasoned financial professional with expertise across quantitative analysis & modeling, risk management (credit, liquidity & market risk), capital market, collateral management, corporate treasury, and enterprise data warehouse.

Prior to his current senior consulting role in risk analytics and regulatory reporting at a major Canadian bank, he also served many senior management roles in Canadian banks, including the director of Treasury and Global Risk Management, and the senior manager in Financial Modeling.

Jonathan is a CFA charterholder. He is also a certified Personal Financial Planner and SAS modeller. He will best leverage his strong cross-business background to present you a good application of financial modeling in Financial Risk Management (FRM), especially in the context of the inter-relationship between regulatory, financial, risk and capital management issues in Financial Institutions.

Moiz Ali, Manager, Analytics & Insights, Scotiabank

A creative professional of business analytics with a proven track record of quickly unearthing and visualizing business insights in vast amounts of data to present to upper management

Currently Moiz is a segmentation analytics manager at Scotiabank International with over 5 years of strategy/consulting experience in retail and banking industry. By leading cross regional projects and focusing on segmentation strategy for Latin American countries, he intensively applies data-driven statistical models and the CRISP (Cross-Industry Standard Process for Data Mining) framework to drive Income based Segmentation and Customer Profitability Segmentation. He is an expert in mining, extracting, analyzing, visualizing, and presenting data from diverse business areas in novel and insightful ways to persuade C-level executives to take informed actions at Scotiabank.

Moiz has a combined background of business and data management. After graduation from U of T with Bachelor of Commerce, specialized in Finance and Economics, he joined Sears as an internal data strategist where he had great opportunities to diagnose, solve and optimize multiple businesses relating but not limited to pricing, promotion, inventory allocation, branch network optimization and supply chain optimization for 2 years. Then he moved to banking industry and worked at Scotiabank in retail pricing department where he heavily experienced in creating business strategies based on large volume data.

During his work tenure, he extensively used tools such as SAS (SAS Advanced Certificate holder), R (Certificated), Tableau, MS Excel (Advanced VBA), Python and Alteryx to drive the analytics on the projects in hand.

Moiz is also a great instructor. His open class for business analytics and career development in retail & banking industry was well received at NHC (new horizon club), especially for new-grads who are looking for BA positions.

David Cui, Senior Data Scientist, Amazon

David is currently a Senior Data Scientist on the forecasting team at Amazon. Prior to joining Amazon, he was the Senior Manager of Marketing Analytics team at RBC, where he focused on statistical analysis, AB testing, and campaign optimization. David has a passion for teaching and he's coached more than 500 students in math and many of his students made into the Canadian International Physics Olympiads team and won contest prizes

Clement Chau, Manager, Advanced Modeling & Analytics, Rogers

Clement is currently working at Rogers as the Manager of Modeling and Analytics team. His job is to help Rogers better understand its customer base and improve campaign targeting by leveraging propensity models to save the company's targeting cost. That implies various tasks from planning, building, scoring, and validating models, reporting & analytics, all the way to working with various data owners (including himself) to make sure all necessary data is available at model scoring time, and working with business partners to promote the proper use of models.

Shaohua Zhang

Cofounder of WeCloudData

A self-trained data scientist and an expert in applied big data technologies, Shaohua has 9 years of experience in applied data science and has built a reputation for building high-performance data science teams. He is currently a senior data scientist at Kik Interactive Inc., helping the billion-dollar Canadian tech unicorn grow its big data initiative.

Prior to Kik, Shaohua built a high-performance data science team at BlackBerry that focused on building innovative data science solutions for marketing, CRM and product teams. His is specialized in user interest graph modelling, targeted advertising, scalable location intelligence and large-scale recommendation engines for mobile personalization. He also collaborated with Ryerson’s Data Science Lab on several big data research projects. Shaohua also helped build the big data course at Ryerson University where he trained over 150 professionals on big data technologies such as Hadoop, Spark and data sciences.

Free this free workshop you will learn:

  • Trends in the job market of Data science and Business Analytics fields
  • How to get prepared for Data Science and Business Analytics jobs - hard skills & soft skills
  • Resume tips - we will randomly select 3 resumes and our speakers will revise them on site
  • How to prepare a data portfolio for your job interviews
  • We answer every question you have regarding the job hunting in data science field

Who should attend:

  • Students from Math, Stats, Computer Science, Finance, Econ, Engineering, Natural Science majors want to find an intern position
  • Fresh graduates who want to explore the potential interests and find a full-time job
  • Professionals who want to switch the careers

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University of Toronto - St. George Campus

27 King's College Circle, GB120

Toronto, ON M5S 3H7


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