Unconventional Journeys: Pathways to Data & AI Careers

Join us for an insightful event delving into unique paths to success in data science and AI. Our diverse panel shares personal stories of discovery, resilience, and innovation, offering valuable insights and practical advice. Connect with industry pioneers, gain inspiration, and chart your own course in the world of data.

Highlights:

• Personal anecdotes from trailblazers in data and AI.
• Insights into diverse backgrounds shaping innovation.
• Practical advice for navigating unconventional paths.
• Networking opportunities with professionals and leaders.

Panelists

Mariam Afshin

Mariam Afshin works as the Director of Data Science in AIOPS, where she sets the strategy and direction to transform IT operations at RBC.

AIOPS develops and applies Machine Learning (ML) and Artificial Intelligence (AI) tools to increase uptime of IT systems, by providing holistic predictive insights and enabling automation of IT operations.

Mariam finished her PhD in Machine Learning and AI at University of Western Ontario and since then has been applying AI and ML tools to real-world problems to generate actionable business insights to drive product and business decisions across multiple industries.

She spends most of her free time with family and friends, voluntary events and enjoying outdoor activities.

Alicia Guo

Data Science Lead at Ernst & Young LLP

Alicia is a data science lead at EY Data & AI Team in Technology Consulting. She has more than 12 years working experience on model lifecycle management and modernization, data and system migration, risk management, and program transformation across industry sectors. Prior to joining EY, she worked in PwC Canada, Mckinsey & Company US and Scotiabank.

She has a PhD in applied mathematics specialized in numerical methods and algorithms development and applications in industry. She is also in Advisory Board of Northeastern University data analytics Master program, working along with senior industry practitioners/tech entrepreneurs to design advanced analytics/data science courses, connecting graduate students with industry professionals, and coaching them in career development.

Lorena Almaraz De La Garza

Senior AI/ML Model Steward Partner at Thomson Reuters

Fluent in “AI Development” and “AI Policy”, Lorena bridges the gap between these two by working directly with engineering and oversight teams. As an AI Governance professional, Lorena’s priority is to ensure that Responsible AI frameworks are not purely aspirational but practical and readily applied. Lorena has a Master of Information from the University of Toronto with concentrations in Human-Centred Data Science and Critical Information Policy. Prior to graduate school, Lorena co-designed and oversaw the delivery of publicly-funded programs in education and culture, and received a Bachelor’s degree in Fine Arts and Cognitive Science from the University of Waterloo. Outside of work, Lorena is a swimmer and aspiring K-pop and ballet dancer.

Denika McPherson

Denika McPherson brings over fourteen years of healthcare experience in critical care, primary care, digital health, academia and operations leadership. Digital health refers to using information and information technology to improve the healthcare system. As a Digital Health AI lead and Senior Business Advisor for the Ontario Government, she navigates the intersection of technology and healthcare, driving healthcare strategy, policy and transformation through digital health innovation. She is also an After-Hours Clinical Manager. Denika is a University of Toronto (U of T) alumnus of the Master of Nursing – Nurse Practitioner Program. She has served as a mentor for three different U of T faculty programs, a contributor and evaluator of provincial digital health best practice guidelines, a provincial innovation challenge competition evaluator, a Guest lecturer at York University on nursing ethics and moral values, a Big Data challenge reviewer for STEM fellowship, and an MIT Hackathon mentor. Outside work, Denika enjoys photography, playing steelpan, high-intensity interval training, visiting museums and libraries, and travelling. She has visited every continent except Antarctica, which is on her list.

Your Moderator : Siphu Langeni

Siphu Langeni is a freelance Data Scientist and AI Consultant, specializing in supporting startups and small to medium-sized enterprises in leveraging their data through AI. Her focus ranges from developing AI strategies to implementing product analytics and deploying ML/AI products.  Previously, Siphu worked at Shopify as a full-stack Data Scientist on the Commerce Algorithms and Capital Algorithms teams. Here, she contributed to building and scaling AI products, empowering merchants to gain a competitive edge in their entrepreneurial endeavors. Notably, her innovative contributions led to her involvement in patenting a color extraction pipeline, enhancing discoverability and product understanding for merchants on the Shopify platform through the United States Patent and Trademark Office (USPTO).  Siphu's career journey is marked by a commitment to lifelong learning and a bold transition from a rewarding role as a Certified Registered Nurse Anesthetist (CRNA), following the completion of her Master of Science in Anesthesia from the University of Michigan - Flint. Her interest in data was sparked during her clinical practice in anesthesia, critical care and trauma, where she recognized the profound impact data could have on patient outcomes, hospital policies and cost savings.  Outside of her professional endeavors, Siphu is passionate about shaping the next generation of data professionals. She dedicates her spare time to mentoring and instructing at Lighthouse Labs, where she has contributed as a subject matter expert for curriculum development in their Data Analytics and Data Science bootcamps.

Don't miss this chance to explore unconventional routes to data and AI careers. Reserve your spot today!