Lead Assistant Manager

Job Title: Data Scientist – AI Solutions

Business Unit:

Primary Domain:

Job Summary

EXL Digital

Data Scientists

Natural Language Processing (NLP)

Large Language Models (LLMs)

insurance and other domains

Key Responsibilities

• Design, develop, and deploy AI/NLP solutions to solve diverse business challenges—particularly in areas like text classification, information extraction, summarization, and semantic search
• Own the full model development lifecycle:
• Select appropriate algorithms (rule-based, statistical, deep learning, transformer-based)
• Conduct exploratory data analysis and feature engineering
• Train and fine-tune models using tools such as Hugging Face Transformers, spaCy, and open-source LLMs
• Integrate external ontologies, taxonomies, and domain knowledge for enhanced performance
• Validate and monitor solution quality using real-world feedback data
• Work closely with ML engineers and DevOps teams to operationalize models (on cloud and on-prem environments)
• Hands-on experience on deploying solutions to cloud-native AI platforms capable of handling large-scale data pipelines and complex machine learning models (AWS/Azure/GCP)
• Collaborate with clients and business stakeholders to scope and refine requirements, validate model behavior, and ensure successful deployment
• Explore and experiment with LLM fine-tuning, prompt engineering, and retrieval-augmented generation (RAG) techniques for advanced use cases
• Contribute to building reusable components, best practices, and scalable frameworks for AI delivery
  

Qualifications

• 4–8 years of hands-on experience in data science, with a focus on NLP, deep learning, and machine learning applications
• Strong programming skills in Python; experience with relevant libraries such as scikit-learn, spaCy, NLTK, PyTorch, TensorFlow, or Hugging Face
• Proven experience in delivering NLP/LLM-based solutions, preferably involving unstructured data from insurance or financial services
• Familiarity with cloud platforms (AWS, Azure, or GCP) and experience with deploying AI models to production
• Ability to handle end-to-end ownership of solutions, from POC to deployment
• Prior experience in consulting or client-facing data science roles is a plus
• Exposure to document databases (e.g., MongoDB), graph databases, or vector databases (e.g., FAISS, Pinecone) is a bonus
• Education: Bachelor’s or Master’s degree in Engineering, Computer Science, Statistics, or a related field; MBA or degree from Tier 1 institution is a plus
  

What We Offer

• Work on real-world AI projects that go beyond experimentation—drive live deployments with business impact
• Access to top-tier mentorship, training, and learning opportunities in AI/ML/NLP and cloud technologies
• Exposure to a wide variety of business use cases in insurance, healthcare, and financial services
• A collaborative, fast-paced, and intellectually stimulating environment
• Structured career growth paths, with opportunities to develop technical and business consulting expertise
• Be part of a global team of AI/ML professionals, working at the cutting edge of innovation