Description

Design and deploy intelligent models using advanced statistical techniques, traditional machine learning, deep learning, and modern approaches like Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI.

This role is on-site.

Responsibilities

• Lead cross-functional discovery sessions to translate business challenges into actionable analytical objectives.
• Develop end-to-end modelling pipelines encompassing sampling design and selection of appropriate statistical and AI methodologies.
• Collaborate with data stewards and engineering teams to curate high-quality datasets for model development.
• Monitor and refine model performance through continuous evaluation and adaptive learning mechanisms.

Required Skills

• Advanced degree in Applied Mathematics, Physics, Computer Science, Statistics, or a related technical field.
• Proficiency in traditional machine learning and statistical modelling, including regression, classification, and sampling design.
• Strong coding skills in Python, SQL, PyTorch, and TensorFlow.
• 5+ years of experience transitioning projects from proof-of-concept to production.
• Demonstrated experience with LLM technologies, RAG, and GenAI frameworks.
• Systems-level thinking with a track record of creative problem-solving.

Preferred Skills

• Experience with Agentic AI architectures.
• Proven ability to document processes for reproducibility and auditability.

Key Skills

Education

Bachelor's degree