Pathways to Success: Navigating Roles, Learning, and Certifications

Is it better to work at a startup vs. big tech? Maggie outlines the unique challenges, opportunities, and cultural differences between these environments, from the broad scope of tasks at startups to the specialized roles in big tech. Maggie also offers advice on evaluating the vast landscape of data science courses, focusing on relevance, industry recognition, and practical application to ensure you're investing in skills that matter. Whether you're deciding between the dynamic pace of startups or the structured innovation of big tech, or navigating educational options, this episode is your guide to making informed choices.

Class Description

Explore the fascinating world of data science through Maggie's inspiring journey in this talk series. Maggie's unconventional path from geography to data science reveals valuable lessons for everyone, regardless of their career aspirations. Discover the importance of embracing opportunities and going beyond your comfort zone, whether you're aiming for a career in data science or simply seeking personal and professional growth. Maggie shares insights on diverse data science roles, essential skills for success, and the significance of mentorship. Gain practical wisdom on evaluating courses and certifications, making informed career decisions, and navigating life's defining moments.


Maggie is a dedicated data scientist with expertise in data science and spatial statistics, primarily within the logistics industry. She excels at bridging the gap between algorithms and product development, collaborating closely with cross-functional teams to drive innovation.

Maggie is pursuing advanced studies in artificial intelligence through graduate-level courses at Stanford University. She's particularly interested in harnessing movement data to enhance daily lives through machine learning applications. Maggie's journey embodies her commitment to excellence and innovation in the data science field, with a goal to make a meaningful impact on the world through data-driven solutions.

Data Analysis
Geographic Information Systems (GIS)
University of Toronto
Stanford University
Planning Intern, City Planning Division
City of Toronto
External Research Analyst
Data Engineer
EQ Works
Data Scientist