Data Scientist

Key Skills:

Roles & Responsibilities:

• Design, develop, and implement advanced machine learning models and algorithms to solve complex business problems.
• Apply expertise in areas such as Natural Language Processing (NLP), Computer Vision, Recommender Systems, and Predictive Modeling.
• Develop robust, scalable, and maintainable ML solutions for production environments.
• Build and manage end-to-end ML pipelines including data cleaning, feature engineering, model training, validation, and deployment.
• Establish CI/CD pipelines for automated model testing, deployment, and integration.
• Collaborate with cross-functional teams including engineering, product, and platform teams to ensure seamless ML model integration.
• Analyze large-scale datasets to derive actionable insights and improve business outcomes.
• Research and experiment with new algorithms, frameworks, and approaches in areas such as Generative AI and Deep Learning.
• Optimize existing models for performance, scalability, and accuracy.
• Document methodologies, processes, and results to ensure reproducibility and continuous improvement.

Experience Requirement:

• 3 - 7 years of hands-on experience in Data Science and Machine Learning.
• Proven experience in developing and deploying ML models in production.
• Strong programming skills in Python and experience with libraries like Scikit-learn, TensorFlow, or PyTorch.
• Experience with distributed data processing frameworks such as PySpark (nice-to-have).
• Exposure to areas like Recommender Systems, Search, Computer Vision, Pricing, Forecasting, and Generative AI.
• Understanding of CI/CD, MLOps, and software engineering best practices.
• Strong problem-solving, analytical thinking, and collaboration skills.

Education: