Job Description
Key Responsibilities
Advanced Analytics & Data Science
Design and develop
advanced ML, NLP, deep learning, and GenAI models
to solve complex business problems.
Perform
feature engineering, model experimentation, tuning, and validation
to ensure high accuracy and robustness.
Apply statistical and analytical techniques for
predictive, prescriptive, and diagnostic analytics .
Build
domain‑aware models , particularly for insurance, financial services, and operational workflows.
Generative AI & Agentic AI Solutions
Design and implement
Generative AI solutions , including
LLM‑based applications, RAG pipelines, embeddings, and vector databases .
Build and orchestrate
agentic AI workflows , enabling multi‑agent collaboration across enterprise systems.
Implement
prompt engineering, evaluation frameworks, safety guardrails, and performance monitoring
for GenAI systems.
Contribute to
EXL AI accelerators, reusable components, and platform capabilities
Data Engineering & Cloud Enablement
Develop and optimize
data pipelines (batch and streaming)
for large‑scale structured and unstructured data.
Deploy AI models using
containerization, CI/CD pipelines, and MLOps best practices .
Architect and implement solutions on
AWS and/or Azure , leveraging managed AI/ML and data services.
Ensure
security, scalability, reliability, and cost optimization
of deployed solutions.
Software Engineering & Production Readiness
Write
clean, modular, and testable Python code
aligned with EXL engineering standards.
Expose AI capabilities via
APIs and microservices
for enterprise consumption.
Implement
model monitoring, drift detection, logging, and retraining mechanisms .
Support
testing, performance tuning, and production issue resolution .
Collaboration & Technical Leadership
Work closely with
solution architects, product managers, business analysts, and domain SMEs .
Mentor junior team members and contribute to
capability building within EXL’s Data & AI practice .
Participate in
design reviews, agile ceremonies, and technical governance forums .
Drive adoption of
best practices, standards, and responsible AI principles .
Education & Experience
Education
Bachelor’s or Master’s degree in
Computer Science, Data Science, Statistics, Mathematics, or related fields .
Experience
5–8+ years
of experience in
data science, machine learning, or advanced analytics .
Proven experience in
building and deploying production‑grade AI/ML solutions .
Strong exposure to
cloud‑based AI and data platforms .
Hands‑on experience with
NLP, GenAI, or large‑scale data solutions .
Technical Skills
Programming : Python (advanced), SQL
ML & AI : Supervised/unsupervised learning, NLP, deep learning, Generative AI, LLMs
Frameworks : PyTorch / TensorFlow, scikit‑learn, Hugging Face (or equivalent)
Data : ETL pipelines, feature engineering, vector databases
MLOps : Docker, CI/CD, experiment tracking, monitoring
Cloud : AWS and/or Azure AI/ML services
Preferred / Good to Have
Experience with
agentic AI frameworks or orchestration layers
Exposure to
insurance or financial services domain
Contributions to
AI platforms, accelerators, or reusable frameworks
Relevant
Cloud / AI / GenAI certifications
Experience in
client‑facing or consulting roles
Key Competencies
Strong analytical and problem‑solving skills
Engineering rigor with a production mindset
Business‑oriented thinking and outcome focus
Collaboration and mentoring ability
Continuous learning and innovation mindset
Why EXL
Work on
cutting‑edge Data, AI, and Agentic AI solutions
Solve
real‑world, high‑impact business problems
Be part of a
market‑leading Data & AI organization
Opportunity to shape
enterprise AI platforms and future‑ready solutions
