Apply via OneDayHire - Fastest Job Connect Starts Here!

Qualification 1. 6+ years of dedicated professional experience in data science/analytics/engineering, with a dedicated focus on production-level model development and deployment for scalable real-world data/analytics solutions/platforms. 2. Strong understanding of ETL processes, data warehousing, and pipeline design for high-quality data management. 3. Proven working experience in DevOps and MLOps, with hands-on experience in CI/CD for data, analytics, and ML pipelines. 4. Proficiency in Python, SQL, Time-series databases, and MongoDB with extensive hands-on experience in production-grade Machine/Deep Learning libraries/methodologies/models and data engineering tools. 5. Proven development work experience with AWS cloud service and high-level proficiency in using cloud tools or services. 6. Solid understanding and proven experience in statistical methods/modeling, machine/deep learning, data preprocessing, and feature engineering. 7. Solid understanding of deep learning architectures relevant to time-series data analysis. 8. Solid understanding and proven work experience in database/data pipeline design, engineering, deployment, and maintenance. 9. Willingness to work in a fast-paced, high-growth environment 10. Experience with backend development frameworks (Fast API, Django, Flask, Node.Js, etc.) for deploying data services. Nice to have 1. Working knowledge of big data technologies (e.g., Spark, Hadoop) for scaling ML and data processing tasks. 2. Experience with frontend development frameworks for visualization (React, etc.). What will we do together? 1. Design, build, and optimize data pipelines for cleaning, processing, and feature extraction from large datasets and live data streams. 2. Design, develop, deploy, and maintain ML models and data analytics services. 3. Collaborate closely with Data Scientists/Engineers and Software Engineers to integrate ML models and data analytics services with cloud-based systems. 4. Design and Build necessary infrastructure/stack to facilitate smooth and reliable functioning of analytics and other data processing services. 5. Support cross-functional teams by providing technical expertise and insight into complex data-driven challenges. 6. Closely work with the Data Scientists/Analysts/domain experts and supervise/assist them on activities related to data analytics services/solutions design, development, and deployment. 7. Provide technical support and required supervision wherever necessary. 8. Maintain thorough documentation for models, data processes, data services design decisions, and algorithmic decisions, etc.. 9. Provide mentorship to junior data science team members, fostering a collaborative and innovative team environment. Job Location New Delhi, India (Primary Location)