Jennifer LaPlante, acknowledged in the DataIQ 100 – Digital Nova Scotia – Leading Digital Industry
Jennifer LaPlante, acknowledged in the DataIQ 100

February 4, 2021

Digital Nova Scotia member and Executive Director of the oceantech artificial intelligence organization DeepSense, Jennifer LaPlante has been named in the DataIQ 100, a list of the world’s most influential data and analytics practitioners.

Since 2014, DataIQ is the first and only fully-curated power list of the most influential data and analytics practitioners. It has been tracking the rise of chief data officers, chief analytics officers, data scientists, data governance experts and the leaders of key vendors and service providers. Inclusion in the DataIQ 100 is a notable badge of honour that is widely referenced by the individuals who make the cut.

“Being named in the DataIQ 100 is a great honour for me and the DeepSense team,” said LaPlante in a statement. “We have been working hard to increase comprehension of AI’s potential in growing our ocean economy in Canada.”

DeepSense was created to enable the ocean sector to explore, attempt and adopt AI and machine learning. We have the dual purpose of identifying and completing projects with graduate students and ocean sector companies to develop a proof of concept, AI prototype or functional code to help optimize operations and create a new product or service. At the same time, we are focused on demonstrating to students the breadth of companies and industries that will benefit from their skills, increasing supply of talent as demand in the sector for data skills grows.

In addition to DeepSense, LaPlante and Sreejata Chatterjee, Co-Founder and Head of Product at Halifax-based LeadSift, have established the Halifax chapter of Women in Machine Learning and Data Science, which now has more than 230 members. They wanted an organization in which women or gender minorities could learn about AI, machine learning and data science without being overwhelmed by men already steeped in these disciplines.

LaPlante said the Women in Machine Learning group is divided evenly between: women working in the field; women who are familiar with the science but not working in it; and women who are new to it. The vast majority are new Canadians, she said, and the group aims to create a collegial environment in which everyone can learn.

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