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Position: Lead Data/ML Engineer
Institution: Mastercard
Location: Pune, India
Duties: As a Lead ML/Data Learning Engineer Leader in the Data Engineering & Analytics team, you will develop data & analytics solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge analytical techniques including machine learning and artificial intelligence, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high-performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data
Requirements: Experience leveraging open-source tools, predictive analytics, machine learning, Advanced Statistics, and other data techniques to perform basic analyses; At least 10 years of relevant hands-on experience as a Data Engineer in an individual contributor capacity; At least 5 year leading collaborative work in complex engineering projects in an Agile setting e.g. Scrum
   
Text: Lead Data/ML Engineer As a Lead ML/Data Learning Engineer Leader in the Data Engineering & Analytics team, you will develop data & analytics solutions that sit atop vast datasets gathered by retail stores, restaurants, banks, and other consumer-focused companies. The challenge will be to create high-performance algorithms, cutting-edge analytical techniques including machine learning and artificial intelligence, and intuitive workflows that allow our users to derive insights from big data that in turn drive their businesses. You will have the opportunity to create high-performance analytic solutions based on data sets measured in the billions of transactions and front-end visualizations to unleash the value of big data Experience leveraging open-source tools, predictive analytics, machine learning, Advanced Statistics, and other data techniques to perform basic analyses; At least 10 years of relevant hands-on experience as a Data Engineer in an individual contributor capacity; At least 5 year leading collaborative work in complex engineering projects in an Agile setting e.g. Scrum
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