Lead Data Scientist (Gen AI)

The core responsibilities for the job include the following:

Key / Primary Responsibilities:

• Leading the end-to-end lifecycle of advanced Gen AI projects, including scoping, solution design, delivery, and deployment within cross-functional teams.
• Defining data science best practices, code quality standards, and technical governance across the team.
• Expert-level proficiency in Python or R, with deep experience in data science libraries such as pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch, and Keras.
• Overseeing the adoption and optimization of Natural Language Processing (NLP) solutions, including frameworks like NLTK, SpaCy, Gensim, as well as advanced transformer models (BERT, GPT, LLMs).
• Architecting and guiding the implementation of large-scale text analytics systems (topic modeling, sentiment analysis, text classification, and semantic search).
• Ensuring robust model management, reproducibility, and effective MLOps in cloud (AWS, Azure, GCP) and on-premise infrastructures.
• Advanced SQL and NoSQL expertise, and hands-on use of orchestration and workflow automation tools (Airflow, Control-M).

Secondary Responsibilities:

• Mentoring and upskilling data scientists, reviewing code and solutions, and providing technical leadership on multiple concurrent projects.
• Shaping data flow designs for large-scale, unstructured data; championing data quality and integrity standards.
• Driving model validation, monitoring, and continuous improvement for production workloads.