Senior Data Scientist - Machine Learning

Job Title : Senior Data Scientist

Location : Onsite Bangalore

Experience : 7+ 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.