Sr. Data Scientist-Stratup-Mid-Size companies Exp.@ Bangalore_Urgent Bean Hr Consulting

8.0 - 13.0 years

30 - 40 Lacs

Bengaluru

Work from Office

Senior Data Scientist Location: Onsite Bangalore Experience: 8+ years Role Overview We are seeking a Senior Data Scientist with a strong foundation in machine learning, deep learning, and statistical modeling, with the ability to translate complex operational problems into scalable AI/ML solutions. In addition to core data science responsibilities, the role involves building production-ready backends in Python and contributing to end-to-end model lifecycle management. Exposure to computer vision is a plus, especially for industrial use cases like identification, intrusion detection, and anomaly detection. Key Responsibilities Develop, validate, and deploy machine learning and deep learning models for forecasting, classification, anomaly detection, and operational optimization Build backend APIs using Python (FastAPI, Flask) to serve ML/DL models in production environments Apply advanced computer vision models (e.g., YOLO, Faster R-CNN) to object detection, intrusion detection, and visual monitoring tasks Translate business problems into analytical frameworks and data science solutions Work with data engineering and DevOps teams to operationalize and monitor models at scale Collaborate with product, domain experts, and engineering teams to iterate on solution design Contribute to technical documentation, model explainability, and reproducibility practices Required Skills Strong proficiency in Python for data science and backend development Experience with ML/DL libraries such as scikit-learn, TensorFlow, or PyTorch Solid knowledge of time-series modeling, forecasting techniques, and anomaly detection Experience building and deploying APIs for model serving (FastAPI, Flask) Familiarity with real-time data pipelines using Kafka, Spark, or similar tools Strong understanding of model validation, feature engineering, and performance tuning Ability to work with SQL and NoSQL databases, and large-scale datasets Good communication skills and stakeholder engagement experience Good to Have Experience with ML model deployment tools (MLflow, Docker, Airflow) Understanding of MLOps and continuous model delivery practices Background in aviation, logistics, manufacturing, or other industrial domains Familiarity with edge deployment and optimization of vision models Qualifications Masters or PhD in Data Science, Computer Science, Applied Mathematics, or related field 7+ years of experience in machine learning and data science, including end-to-end deployment of models in production

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