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Azure Data Scientist Surat (India)

IndiaPosted 1 month ago
Data Science And StatisticsJuniorFull Time; Regular
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About Smart Working At Smart Working, we believe your job should not only look right on paper but also feel right every day. This isn t just another remote opportunity - it s about finding where you truly belong, no matter where you are. From day one, you re welcomed into a genuine community that values your growth and well-being. Our mission is easy: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles. We help you discover meaningful work with teams that invest in your success, where you re empowered to grow personally and professionally. Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world. About the Role We re looking for a DP-100-certified Azure Data Scientist who is passionate about applied Machine Learning and delivering measurable improvements for clients through smart, productive, and scalable solutions. You ll be part of a growing innovation and technology team, contributing to the design, training, and deployment of AI and ML models within the Azure ecosystem. Using your expertise in Azure Machine Learning, Python (pandas, scikit-learn), and Azure SDKs, you ll help shape our data and productivity capabilities integrating ML models into real business processes that drive meaningful outcomes. This role is ideal for someone who combines technical depth, curiosity, and a commitment to continuous learning, eager to build a long-term career in a forward-thinking, collaborative workplace. Responsibilities Work directly with business stakeholders to design and deliver end-to-end machine learning solutions aligned with operational and governance standards. Prepare and transform datasets for modelling using Python and Azure-native tools, ensuring data quality and consistency across the ML lifecycle. Build, evaluate, and deploy models using AutoML, MLflow, and custom pipelines, focusing on per .

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