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An innovative digital consultancy is seeking a Staff Data Scientist / ML Engineer to join a dynamic team. This role involves designing and delivering machine learning solutions, tackling complex datasets, and collaborating with a skilled team. The company offers a flexible work environment, allowing for remote work while fostering a culture of innovation and excellence. You will have the opportunity to work with leading brands and cutting-edge technologies, making a significant impact in the digital landscape. If you're passionate about data science and eager to contribute to transformative projects, this role is perfect for you.
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Who We Are
Welcome to
Data Scientist / ML Engineer (Staff)
Who We Are
Welcome to TELUS Digital, where innovation meets impact. As an award-winning digital product consultancy, we're shaping the future of digital experiences through cutting-edge technology, agile thinking, and a culture that puts people first.
We are the global digital section of TELUS, one of Canada’s largest telecommunications providers. Our global teams deliver transformative digital solutions and customer experiences for industry leaders in consumer electronics, finance, telecommunications, and utilities. With robust multi-shore delivery capabilities, multi-language programs, and secure infrastructure, we ensure exceptional service backed by our multi-billion-dollar parent company.
Location and Flexibility
This role can be fully remote for candidates based in the states of São Paulo and Rio Grande do Sul as well as in the cities of Rio de Janeiro, and Belo Horizonte, due to team distribution and occasional in-person opportunities. If you are based in São Paulo or Porto Alegre, you are welcome to work from one of our offices on a flexible schedule.
The Opportunity
As a Data Scientist / Machine Learning Engineer on our team, you'll design, develop, and deliver machine learning solutions, decipher loosely defined problems using complex datasets, and determine appropriate analytical and modeling techniques. You'll analyze structured and unstructured data, establish automated processes for large-scale modeling, perform exploratory analysis, and collaborate with peers on data acquisition and exploration, demonstrating a strong sense of ownership and urgency.
Responsibilities
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