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 wellbeing Our mission is simple to break down geographic barriers and connect skilled professionals with outstanding global teams and products for fulltime longterm 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 highestrated workplaces on Glassdoor and experience what it means to thrive in a truly remotefirst world About the Role We re looking for a DP100certified Azure Data Scientist who is passionate about applied Machine Learning and delivering measurable improvements for clients through smart efficient 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 scikitlearn 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 longterm career in a forwardthinking collaborative workplace Responsibilities Work directly with business stakeholders to design and deliver endtoend machine learning solutions aligned with operational and governance standards Prepare and transform datasets for modelling using Python and Azurenative tools ensuring data quality and consistency across the ML lifecycle Build evaluate and deploy models using AutoML MLflow and custom pipelines focusing on performance scalability and maintainability Implement monitoring and retraining strategies to detect drift and maintain model accuracy over time Apply responsible AI principles fairness explainability and privacy throughout model development Collaborate with crossfunctional teams to integrate ML and AI solutions into business workflows enhancing decisionmaking engagement and productivity Support clients in maintaining and optimising Azure ML environments for reproducible experimentation and efficient deployment Contribute to MLOps implementation including CI CD pipelines model registry and environment management across dev test prod environments Work with tools such as Azure DevOps GitHub Actions Azure Storage and Power BI Fabric to ensure solutions are productionready and observable Stay current with emerging Azure AI technologies contributing to the continuous improvement of our machine learning practices Requirements Microsoft Certified Azure Data Scientist Associate DP100 mandatory 2 years of experience in applied machine learning or data science delivering productiongrade ML solutions Handson experience designing training and deploying models using Azure Machine Learning AML AutoML and MLflow Proficiency in Python pandas and scikitlearn for feature engineering model training and rigorous validation Proven ability to deploy models to realtime REST endpoints and orchestrate batch inference pipelines Experience implementing MLOps practices including CI CD pipelines model registries and automated retraining Understanding of Azure cloud and data engineering concepts including compute storage and orchestration services Strong collaboration skills able to work with subject matter experts to translate business processes into ML opportunities with measurable impact Excellent communication and problemsolving abilities with confidence engaging technical and nontechnical audiences Knowledge of responsible and ethical AI frameworks ensuring transparency and compliance in model development Nice to Have Exposure to Kubernetes Azure AI Search or Azure AI Foundry for scalable ML deployments Familiarity with generative AI techniques and language model optimisation Experience integrating analytics or model outputs into Power BI or Azure Fabric dashboards Understanding of Azure cost governance and performance optimisation for ML workloads Broader knowledge of data governance and security principles in AIdriven environments Responsible AI Azure ML environment optimisation business workflow integration with ML staying current with emerging Azure AI t

📌 Azure Data Scientist AI and ML (Vijayawada)
🏢 SWS Smart Working Solutions
📍 Vijayawada