About Smart WorkingAt Smart Working, we believe your job should not only look right on paper but also feel right every day. This isnt just another remote prospect - its about finding where you truly belong, no matter where you are. From day one, youre welcomed into a genuine community that values your growth and well-being.Our mission is simple: 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 youre 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 RoleWere looking for a DP-100certified Azure Data Scientist who is passionate about applied Machine Learning and delivering measurable improvements for clients through smart, productive, and scalable solutions. Youll 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, youll 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 environment.ResponsibilitiesWork directly with business stakeholders to design and deliver end-to-end machine learning solutions aligned with operational and governance standardsPrepare and transform datasets for modelling using Python and Azure-native tools,



ensuring data quality and consistency across the ML lifecycleBuild, evaluate, and deploy models using AutoML, MLflow, and custom pipelines, focusing on performance, scalability, and maintainabilityImplement monitoring and retraining strategies to detect drift and maintain model accuracy over timeApply responsible AI principles fairness, explainability, and privacy throughout model developmentCollaborate with cross-functional teams to integrate ML and AI solutions into business workflows, enhancing decision-making, engagement, and productivitySupport clients in maintaining and optimising Azure ML environments for reproducible experimentation and efficient deploymentContribute to MLOps implementation, including CI/CD pipelines, model registry, and environment management across dev/test/prod environmentsWork with tools such as Azure DevOps, GitHub Actions, Azure Storage, and Power BI/Fabric to ensure solutions are production-ready and observableStay current with emerging Azure AI technologies, contributing to the continuous improvement of our machine learning practicesRequirementsMicrosoft Certified: Azure Data Scientist Associate (DP-100) mandatory2 years of experience in applied machine learning or data science, delivering production-grade ML solutionsHands-on experience designing, training, and deploying models using Azure Machine Learning (AML), AutoML, and MLflowProficiency in Python, pandas,



and scikit-learn for feature engineering, model training, and rigorous validationProven ability to deploy models to real-time REST endpoints and orchestrate batch inference pipelinesExperience implementing MLOps practices, including CI/CD pipelines, model registries, and automated retrainingUnderstanding of Azure cloud and data engineering concepts, including compute, storage, and orchestration servicesStrong collaboration skills able to work with subject matter experts to translate business processes into ML opportunities with measurable impactExcellent communication and problem-solving abilities, with confidence engaging technical and non-technical audiencesKnowledge of responsible and ethical AI frameworks, ensuring transparency and compliance in model developmentNice to HaveExposure to Kubernetes, Azure AI Search, or Azure AI Foundry for scalable ML deploymentsFamiliarity with generative AI techniques and language model optimisationExperience integrating analytics or model outputs into Power BI or Azure Fabric dashboardsUnderstanding of Azure cost governance and performance optimisation for ML workloadsBroader knowledge of data governance and security principles in AI-driven environmentsResponsible AI, Azure ML environment optimisation, business workflow integration with ML, staying current with emerging Azure AI technologyBenefitsFixed Shifts: 12:00 PM - 9:30 PM IST (Summer) | 1:00 PM - 10:30 PM IST (Winter)No Weekend Work: Real work-life balance, not just wordsDay 1 Perks: Laptop and full medical insurance providedSupport That Matters:Mentorship, community, and forums where ideas are sharedTrue Belonging: A long-term career where your contributions are valuedAt Smart

📌 Azure Data Scientist (AI & ML) (Remote, Full-Time), India
🏢 Smart Working
📍 Chennai