Mississauga, CAN
1 day ago
System and Data Engineer
Xylem is a Fortune 500 global water solutions company dedicated to advancing sustainable impact and empowering the people who make water work every day. As a leading water technology company with 23,000 employees operating in over 150 countries, Xylem is at the forefront of addressing the world's most critical water challenges. We invite passionate individuals to join our team, dedicated to exceeding customer expectations through innovative and sustainable solutions. **Pure Technologies** (https://www.xylem.com/en-us/brands/pure-technologies/), a Xylem brand under Utility Services, WSS, is a world leader in the development and application of innovative technologies and solutions. With a focus on sustainability and the environment, Pure is committed to finding and advancing technology-driven services and groundbreaking products for water infrastructure and pipeline owners. We believe our people are the key to our success and take pride in the growth and development of our employees. **The Role:** Xylem Assessment Services under Utility Services, WSS is seeking candidates with a Machine Learning / Data Engineering background to join our team as a **System and Data Engineer** . As a member of our product management and development team, you will be responsible for the design, development and testing of data engineering algorithm and models, and the implementation of Machine Learning applications for specific products, solutions and innovation projects. **Core Responsibilities:** + Organize, manipulate, filter, and visualize a large quantity of data from different products and sensing technologies + Work closely with other engineering teams (software, electrical and mechanical engineers), product owners and other stakeholders to design and develop algorithms and mathematical models to optimize and automate data acquisition, generation, processing, analysis and reporting + Work independently or closely with other data scientists to develop AI, ML, and deep learning models that meet product development requirements while supporting real time monitoring, predictive analysis, feature recognition and extraction etc. + Deliver developed algorithm, models and software products to our operational team (data analysis and field engineering) to meet the development requirements while training and supporting the end users **Required Qualifications:** + Bachelor’s degree in Computer Science, Data Science, Applied Math, Engineering, Physics or other related science or engineering fields. Master of Science preferred. + 2+ years hands-on programming experience with strong development skills in Python, Matlab, C++, C#, or Java. + Creative problem solver with key attention to detail and strong analytical skills to make data-driven decisions. + Strong understanding of statistics, linear algebra and calculus. + Broad knowledge of signal processing, time series and spectral analysis + Excellent communication and documentation skills. + Superior time management skills, tasks prioritization skills and ability to work independently + Ability to multi-task and work in a multi-project development environment + Self-motivated / able to learn new concepts quickly and effectively **Preferred Qualifications:** + Experience with R&D, high-speed data acquisition systems, fast prototyping, and agile development + Experience with acoustic, electromagnetic, and ultrasonic sensors or general sensing technologies preferred Join the global Xylem team to be a part of innovative technology solutions transforming water usage, conservation, and re-use. Our products impact public utilities, industrial sectors, residential areas, and commercial buildings, with a commitment to providing smart metering, network technologies, and advanced analytics for water, electric, and gas utilities. Partner with us in creating a world where water challenges are met with ingenuity and dedication; where we recognize the power of inclusion and belonging in driving innovation and allowing us to compete more effectively around the world.
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