Senior Data Scientist (6-9 years)

Overview

Key Responsibilities:

• Design and develop ML, NLP, and GenAI models to solve real-world business problems.
• Build, train, and fine-tune AI models using Python and leading ML frameworks.
• Leverage Azure and GCP AI/ML services for scalable and production-ready deployment.
• Develop and integrate APIs for real-time model inference and intelligent decision-making.
• Handle large-scale datasets to extract insights and drive data-informed strategies.
• Work collaboratively with Data Engineers, Software Developers, and Product Teams to integrate AI solutions into existing products and platforms.
• Implement and maintain CI/CD pipelines for model development and deployment automation.
• Follow Agile methodologies and adhere to software engineering best practices.
• Stay current with AI/ML innovations, including LLMs and GenAI advancements, and incorporate them into ongoing projects.
• Lead research initiatives and contribute to innovative solution development.
• Provide mentorship to junior team members and ensure knowledge sharing.
• Continuously monitor and optimize models for performance and scalability in production.

Required Skills & Qualifications:

• Proficiency in Python and experience with TensorFlow, PyTorch, or Scikit-learn.
• In-depth understanding of NLP techniques, such as transformers, embeddings, and text analytics.
• Proven expertise in Generative AI models (e.g., GPT, BERT, LLMs).
• Strong experience with Azure AI/ML services (Azure ML, Cognitive Services, Databricks).
• Hands-on experience with GCP AI/ML tools such as Vertex AI, BigQuery ML, and TensorFlow on GCP.
• Proficient in building and integrating REST APIs for ML model inference.
• Familiarity with CI/CD practices tailored for ML environments.
• Strong grasp of software engineering principles (version control, modularity, testing).
• Experience working in Agile development environments.
• Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment.
• Solid background in statistical analysis, data mining, and data visualization.

Preferred Qualifications:

• Experience with MLOps and end-to-end model lifecycle automation.
• Knowledge of vector databases and Retrieval-Augmented Generation (RAG).
• Familiarity with big data processing frameworks such as Apache Spark and Hadoop.
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Exposure to Graph Neural Networks (GNNs) and recommendation engines.
• Understanding of AutoML frameworks and advanced hyperparameter tuning techniques.

Job Type: Contractual / Temporary

Pay: ₹700.00 - ₹900.00 per hour

Experience:

• Python : 6 years (Required)
• TensorFlow: 6 years (Required)
• PyTorch: 6 years (Required)
• Scikit-learn: 6 years (Required)

Work Location: In person