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Senior AI/Data Scientist with 8+ years of experience building scalable machine learning, analytics, and enterprise AI systems. Led production-grade GenAI and agentic AI applications using LangGraph, AWS Bedrock, RAG pipelines, and vector databases, with a strong focus on performance, evaluation, and deployment. Brings a strong background in scalable ML systems, risk analytics, optimization, and technical leadership—backed by international research experience in France and Austria and an IIT Kanpur engineering education. Passionate about responsible AI governance, cross-functional delivery, and turning complex data problems into reliable production solutions.…Senior AI/Data Scientist with 8+ years of experience building scalable machine learning, analytics, and enterprise AI systems. Led production-grade GenAI and agentic AI applications using LangGraph, AWS Bedrock, RAG pipelines, and vector databases, with a strong focus on performance, evaluation, and deployment. Brings a strong background in scalable ML systems, risk analytics, optimization, and technical leadership—backed by international research experience in France and Austria and an IIT Kanpur engineering education. Passionate about responsible AI governance, cross-functional delivery, and turning complex data problems into reliable production solutions.

Indra Kanshana

AI Engineer, Data Scientist, Data Engineer, +2

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Senior AI/Data Scientist with 8+ years of experience building scalable machine learning, analytics, and enterprise AI systems. Led production-grade GenAI and agentic AI applications using LangGraph, AWS Bedrock, RAG pipelines, and vector databases, with a strong focus on performance, evaluation, and deployment. Brings a strong background in scalable ML systems, risk analytics, optimization, and technical leadership—backed by international research experience in France and Austria and an IIT Kanpur engineering education. Passionate about responsible AI governance, cross-functional delivery, and turning complex data problems into reliable production solutions.…Senior AI/Data Scientist with 8+ years of experience building scalable machine learning, analytics, and enterprise AI systems. Led production-grade GenAI and agentic AI applications using LangGraph, AWS Bedrock, RAG pipelines, and vector databases, with a strong focus on performance, evaluation, and deployment. Brings a strong background in scalable ML systems, risk analytics, optimization, and technical leadership—backed by international research experience in France and Austria and an IIT Kanpur engineering education. Passionate about responsible AI governance, cross-functional delivery, and turning complex data problems into reliable production solutions.

Available to hire

Senior AI/Data Scientist with 8+ years of experience building scalable machine learning, analytics, and enterprise AI systems. Led production-grade GenAI and agentic AI applications using LangGraph, AWS Bedrock, RAG pipelines, and vector databases, with a strong focus on performance, evaluation, and deployment.

Brings a strong background in scalable ML systems, risk analytics, optimization, and technical leadership—backed by international research experience in France and Austria and an IIT Kanpur engineering education. Passionate about responsible AI governance, cross-functional delivery, and turning complex data problems into reliable production solutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Beginner

Work Experience

GenAI Tech Lead / AI/ML Consultant at Numantra Technologies

January 1, 2025 - Present

Architected and deployed a production multi-agent AI dashboard for healthcare supply chain analytics using LangGraph, AWS Bedrock, Flask, DuckDB, and Redis. Built an agentic workflow that converts natural language into SQL/visualizations and supported real-time inventory and consumption rate analytics with duplicate detection for ordering. Implemented Docker-based deployment on AWS EC2 with Nginx/Gunicorn reverse proxy, CI/CD workflows, LangSmith observability, and event-driven orchestration with Redis caching to reduce analyst query time from hours to seconds. Built an enterprise RAG knowledge management system ingesting SharePoint documents into FAISS/Chroma vector stores with AWS Bedrock LLMs, using Streamlit UI and S3-based automated workflows, plus Microsoft Teams integration for company-wide discovery. Led cross-functional governance and risk controls for responsible AI. Also built production ETL/ELT pipelines using Azure Data Factory and Databricks, automating Trial Statement Re

Senior Data Scientist / Team Lead at EXL Analytics

March 1, 2024 - November 1, 2024

Led a technical team of 2–3 junior engineers, providing mentorship on advanced analytics and scalable solution delivery for a US bank. Designed and implemented data ingestion and transformation workflows using Databricks (PySpark) and SQL for risk analytics, including Probability of Default (PD) computations for regulatory compliance. Architected high-performance ETL/ELT pipelines incorporating Azure Data Factory triggers and Azure Data Lake to ensure end-to-end data integrity. Developed automated data pipelines and validation layers for CCAR/CECL regulatory reporting using Azure SQL, Databricks, and Azure DevOps CI/CD, improving processing efficiency by 50%.

Graduate Researcher at LMFL – Laboratoire de Mécanique des Fluides de Lille

October 1, 2021 - February 1, 2024

Analyzed turbulent flow data using advanced statistical techniques including autocorrelation, PCA, FFT, Markovianity, probability density functions (PDFs), and higher-order moments to extract insights. Implemented stepwise regression and stochastic modeling for rare event prediction with prediction error within 20%. Optimized object-oriented Python code with parallel processing to improve runtime for large-scale computational workflows. Presented findings at conferences and prepared a manuscript for submission to Physical Review E.

Machine Learning Intern at IST Austria

April 1, 2021 - September 1, 2021

Applied deep learning (autoencoders and PCA) in Python for dimensionality reduction and feature extraction of shear flow dynamics. Tuned hyperparameters using KerasTuner with random search across 100+ models. Achieved a 2-dimensional representation retaining over 75% variance, improving interpretability and efficiency compared to a 5-dimensional PCA baseline.

Machine Learning Intern at LISN – LIMSI, CNRS

April 1, 2020 - September 1, 2020

Developed a CNN in TensorFlow for predicting global heat transfer in turbulent convection from shadowgraph images, achieving strong predictive performance (correlation coefficient 94.1% and R² of 0.885). Implemented preprocessing including normalization and data augmentation with mirrored fields for improved generalization. Applied L1/L2 regularization, dropout, and early stopping to mitigate overfitting, and leveraged GPU deployment for faster computation.

Data Scientist / Lead Assistant Manager at EXL Analytics

March 1, 2017 - June 1, 2019

Developed credit risk models (Static Pool, PDxEADxLGD, State Transition Matrix) for a credit card portfolio to support CECL regulatory compliance in collaboration with TransUnion. Built and validated CCAR models for a major US bank, performing stress testing under diverse macroeconomic scenarios. Designed a synthetic control population using stratified sampling and conducted A/B testing to assess the impact of trigger campaigns.

NLP Data Scientist at Quiklo

October 1, 2016 - February 1, 2017

Performed NLP-based customer interaction analysis using NLTK and built predictive models for customer acquisition targeting. Integrated rule-based conversational chatbot workflows using APIs and Facebook Messenger webhooks.