Past Meetup

Panel Discussion - Data Analyst Career Path

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There’s a lot of interest in becoming a data analyst, and for good reasons: high impact, high job satisfaction, high salaries, high demand... It’s difficult for a beginner to know where to start, and it’s easy to get overwhelmed.

Join us for a Data Analytics Panel Discussion where expert data analysts and hiring managers will share their experience of solving real-world data challenges and their expectations from a data analyst candidate.

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Panel Discussion Topics

- What does it look like to be a data analyst?

- Data analyst vs data scientist vs data engineer?

- Data analytics learning path: How to learn data analytics most efficiently?

- Data analysts in different industries?

- Hiring managers expectation from a data analyst candidate?

- What kind of background is required for a data analyst?

- How to get prepared for data science jobs

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Speakers:

Andreasa | Data Scientist @PayBright

Andresa Andrade enrolled in the Statistics program at University of Campinas. After graduating she tested her skillset by going out into several industries including banking, telecom, retail, technology, and digital. Today, she is a passionate data scientist trying to hover between dealing with gigs of data every day and keeping up with the latest technology. Andresa has a strong background in the following subjects: Big data, predictive analysis, statistics, Naive Bayes, cluster analysis, R (server), SQL, MySQL, SAS, python, Hadoop (Hive and Pig), Adobe Analytics, Adobe Workbench, Adobe Media Optimizer, Adobe Audience Manager, Google Analytics, Google Adwords, Google DoubleClick.

Ken | Data Scientist @Capital One

Ken Ding completed his MBA degree from Rotman School of Business, University of Toronto. Currently, Ken is a Data Scientist at Capital One which is famous for data-driven decision-making. He has over 5 years of experience in data analytics and specializes in credit risk modeling. With a passion for Data Science, Ken has acquired a solid technical background with skills including SQL, Python, SAS, and AWS. Ken enjoys sharing his data science knowledge with everyone.

Moiz | Manager, Analytics and 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. 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.

Eric | Career Coach @WeCloudData

Eric Liu has recently joined WeCloudData to lead the Data Analytics program. He has over 20 years of experience in retail, commercial, and investment banking, highly specialized in data management, descriptive analytics, and predictive modelling. He has taught public speaking at Victoria College, data analytics at George Brown College, retail and commercial banking at York University Schulich Executive Education Centre. Previously, he has worked at Siemens, ING Bank, ING Direct, CIBC, GE Money, Scotiabank (Senior Director), Affirm Financial (Director). Eric holds an EMBA from China Europe International Business School and M.Eng. Operations Research from Huazhong University of Science and Technology.