The inaugural Electron cohort of Cybera’s Applied Data Science Lab for Economic Development launched in October 2022. In this first cohort, nine budding data scientists have been paired with two Alberta-based organizations to begin their real-world data science journey. Over the course of six months, the data science interns will develop and iterate on proof-of-concept data science products and support infrastructure that can be used by their industry partners to improve operations or develop a new product.
The Applied Data Science Lab is designed to help emerging data scientists find employment opportunities by giving them real-world data science experience. In parallel, the program supports Alberta-based organizations to adopt data science practices that will help them de-risk data-related opportunities, improve business productivity, create jobs, secure investment, and improve efficiencies.
Convenient Business Solutions Inc (CBS)
Convenient Business Solutions Inc (CBS) is a software development and optical systems consulting company, located in Edmonton, with clients around the world, including Asia and Europe. The company has developed and commercialized business tools related to property, workflow, human resources, and smart city management, and is looking to leverage AI and machine learning to improve the services it offers to clients.
During this project, the Applied Data Science Lab interns will help CBS find the best way to develop and train their models, improve performance, create pipelines, and scale their cloud environments to support their smart cities initiatives.
Convenient Business Solutions Interns
Neha has a Masters in Arts and Mathematics from the University of Kansas, and is currently a Ph.D. candidate in Mathematical Finance at the University of Alberta. Her Ph.D work involves leveraging data science to research the complexity of the Ergodic process. She had previously worked on Cybera’s Data Science for Albertans program as a fellow with the company Ironsight. In her current internship with CBS, she is gaining experience in object detection and tracking models.
Bahareh received her Ph.D. in Environmental Systems Engineering from the University of Regina and a M.SC in Environmental Engineering from the University of Mazandaran in Iran. Bahareh’s accomplishments include Faculty of Graduate Studies Scholarly Awards and the Regional Centre of Expertise (REC) Sustainability Recognition Award. She recently became a Post-Doctoral associate in the Environmental Data Analyst Department of Geography at the University of Calgary. Bahareh is passionate about coding and generating insights from data, and enjoys working with Cybera to support a project that will have a tangible impact on society.
Vadim has a BSc in Mechanical Engineering and is completing his MSc in Electrical Engineering, with a focus on Software Engineering and Intelligent Systems, at the University of Alberta. He has experience working as a Energy Management Engineer at Capital Power in Edmonton. As part of the Applied Data Science Lab, he enjoys the depth of the project, and the experience he is gaining from the data science team at Cybera.
Gurmol has a Bachelor of Science degree in Biology from the University of Calgary, where he won the Innovation 4 Health competition for his work on a driving app that helped lower the potential for accidents related to pre-existing medical conditions. He also received a Post-Diploma Certificate in Data Analytics from SAIT and completed the Machine Learning technician program at Amii . He previously worked at Motionhall as a Scientific Analyst, and at Longview Systems as a System Consultant.
Minshan has a Master degree in Computer Science from the University of Alberta. While working on her program there, she conducted research in multiple academic projects involving data science and computer vision, and also worked as an intern Machine Learning Developer on a natural language processing machine learning project. She has experience in software development and has successfully developed and deployed several web applications on AWS.
Ziing is a Calgary-based logistics provider, operating across Canada, that helps last mile delivery companies optimize their services and reduce costs. It does this by providing insights on cost efficient delivery planning, integrated processing services, and marketing opportunities.
Through this project, Ziing is looking to develop and optimize its operations through predictive solutions. The data science interns will leverage their collected data to improve the company’s route optimization tool.
Soniya received a Post-Diploma Certificate in Data Analytics from NAIT following her time at APJ Abdul Kalam Technological University, India, where she received a Masters of Technology in VLSI & Embedded Systems. She has experience as a Junior Software Developer at Klocworx Inc, which specializes in electrical engineering for the oil and gas industry. While at Klocworx, she was part of a data logger project for a torque measuring device, which used hardware and software designing and programming with Python and SQL.
Gideon received a PhD in Medicine and a Master of Research (MRes) in Molecular Medicine from Queen's University in Belfast, UK. He has experience as a Research Fellow at The University of British Columbia, Vancouver and Ulster University in Coleraine, UK, where he used research data to generate insights that accelerated drug discovery and repurposing for eye diseases. The greatest benefit he sees from working on the Applied Data Science Lab is collaborating with stakeholders and his team to use data science tools to solve complex problems. These collaborations include discussing project achievements, working together to plan priorities, and working together to overcome obstacles that may be impeding progress.
Feifei received her Ph.D. of Chemistry from the University of New Hampshire, is a joint Postdoc in Chemical and Material Engineering at the University of Alberta, and worked as a postdoc fellow in clinical medicine at Guangzhou Medical University, China. Feifei’s strengths in data science derive from identifying her data science skill gaps, and then conducting online learning or working on self-imposed data science challenges to bridge them.
Binh received a Master of Engineering in Applied Geology & Petroleum Engineering from the Ho Chi Minh University of Technology in Vietnam. He worked as a petroleum geophysicist before moving to Spain, where he learned to code. He used these skills to develop computer vision methods for seismic inversion to invert the seismic data to physical rock properties, the results of which have been published in a scientific petroleum journal. Binh is educated as a full-stack web developer following the completion of a Ubiqum Code Academy bootcamp in Madrid. He moved to Calgary in 2022, where he completed a Machine Learning Technician program at AMII.