Key Responsibilities:

• Design and develop machine learning and deep learning systems using frameworks like TensorFlow, PyTorch, and Scikit-learn.
• Implement real-time systems for forecasting, optimization, and personalized recommendations.
• Research and apply advanced AI/ML techniques, including Generative AI models (e.g., GPT, LLaMA) and NLP architectures.
• Lead end-to-end machine learning projects, from problem framing to deployment and monitoring.
• Manage model lifecycle activities, including training, testing, retraining, and fine-tuning for optimal performance.
• Collaborate with analytics teams, practice leads, subject matter experts, and customer teams to understand business objectives and technical requirements.
• Conduct statistical analysis to address business challenges and drive innovation in AI/ML applications.
• Deploy machine learning applications on cloud platforms (e.g., GCP, Azure, AWS) and ensure seamless integration with existing systems.
• Monitor system performance, address data drift, and ensure scalability and adaptability to evolving requirements.

Qualifications:

• Minimum 7+ years for Principal Data Scientist roles (3+ years for Data Scientist roles) with proven expertise in AI/ML, particularly in Generative AI, NLP, and computer vision.
• Proficient in Python, Java, and R.
• Strong expertise in TensorFlow, PyTorch, Scikit-learn, Django, Flask, Numpy, and Pandas.
• Comprehensive knowledge of data structures, SQL, multi-threading, and APIs (RESTful, OData).
• Hands-on experience with Tableau and Power BI for data visualization.
• Strong understanding of statistics, probability, algorithms, and optimization techniques.
• Experience deploying ML applications on GCP, Azure, or AWS.
• Familiarity with ERP/SAP integration, post-production support, and lifecycle management of ML systems. Industry experience in retail, telecom, or supply chain optimization is a plus.
• Exceptional problem-solving skills, strong leadership capabilities, and excellent communication skills.