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Hi, I’m Chaitanya Prasad Reddy Narala, an AI/ML Engineer with 5 years of experience building and deploying production ML systems for fraud detection, credit risk, and compliance automation. I thrive in highly regulated financial environments and I turn data into AI-powered decision systems using Python, SQL, Spark, Kafka, and cloud-based MLOps on AWS. I aim to deliver faster onboarding, regulator-ready AI, and scalable solutions that improve speed and accuracy. I own end-to-end ML pipelines—from real-time data processing and model deployment to explainability and monitoring. My work has driven meaningful business results, including significant fraud-loss reductions and improved regulatory readiness audits, while maintaining auditability and high availability.…Hi, I’m Chaitanya Prasad Reddy Narala, an AI/ML Engineer with 5 years of experience building and deploying production ML systems for fraud detection, credit risk, and compliance automation. I thrive in highly regulated financial environments and I turn data into AI-powered decision systems using Python, SQL, Spark, Kafka, and cloud-based MLOps on AWS. I aim to deliver faster onboarding, regulator-ready AI, and scalable solutions that improve speed and accuracy. I own end-to-end ML pipelines—from real-time data processing and model deployment to explainability and monitoring. My work has driven meaningful business results, including significant fraud-loss reductions and improved regulatory readiness audits, while maintaining auditability and high availability.

CHAITANYA PRASAD REDDY NARALA

Data Scientist, AI Engineer, Full Stack Developer, +2

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Hi, I’m Chaitanya Prasad Reddy Narala, an AI/ML Engineer with 5 years of experience building and deploying production ML systems for fraud detection, credit risk, and compliance automation. I thrive in highly regulated financial environments and I turn data into AI-powered decision systems using Python, SQL, Spark, Kafka, and cloud-based MLOps on AWS. I aim to deliver faster onboarding, regulator-ready AI, and scalable solutions that improve speed and accuracy. I own end-to-end ML pipelines—from real-time data processing and model deployment to explainability and monitoring. My work has driven meaningful business results, including significant fraud-loss reductions and improved regulatory readiness audits, while maintaining auditability and high availability.…Hi, I’m Chaitanya Prasad Reddy Narala, an AI/ML Engineer with 5 years of experience building and deploying production ML systems for fraud detection, credit risk, and compliance automation. I thrive in highly regulated financial environments and I turn data into AI-powered decision systems using Python, SQL, Spark, Kafka, and cloud-based MLOps on AWS. I aim to deliver faster onboarding, regulator-ready AI, and scalable solutions that improve speed and accuracy. I own end-to-end ML pipelines—from real-time data processing and model deployment to explainability and monitoring. My work has driven meaningful business results, including significant fraud-loss reductions and improved regulatory readiness audits, while maintaining auditability and high availability.

Available to hire

Hi, I’m Chaitanya Prasad Reddy Narala, an AI/ML Engineer with 5 years of experience building and deploying production ML systems for fraud detection, credit risk, and compliance automation. I thrive in highly regulated financial environments and I turn data into AI-powered decision systems using Python, SQL, Spark, Kafka, and cloud-based MLOps on AWS. I aim to deliver faster onboarding, regulator-ready AI, and scalable solutions that improve speed and accuracy.

I own end-to-end ML pipelines—from real-time data processing and model deployment to explainability and monitoring. My work has driven meaningful business results, including significant fraud-loss reductions and improved regulatory readiness audits, while maintaining auditability and high availability.

Skills

Experience Level

Expert

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Language

English

Fluent

Work Experience

AI/ML Engineer at ServiceNow

January 1, 2025 - Present

Built real-time risk scoring and fraud-detection pipelines using Python, XGBoost, Kafka, and SageMaker, reducing fraud losses by 45% across 10M+ annual transactions. Developed an LLM-based KYC copilot using GPT-4o, Claude, and LangChain, automating 70% of compliance workflows and cutting onboarding time by 60%. Designed RAG pipelines with Pinecone, FAISS, and financial data integrations, speeding investigator case-resolution by 50%. Implemented explainability workflows with SHAP and LIME, reducing false positives by 30% and improving auditability for AML and SOC2-aligned review processes. Optimized streaming ML inference on Spark, Databricks, and SageMaker, achieving sub-second latency and improving fraud-model detection accuracy by 40%. Built synthetic fraud-data generation workflows using GANs and diffusion models, improving rare-event detection performance by 35%. Productionized AI services with Docker, Kubernetes, and CI/CD pipelines, improving deployment efficiency by 45% and supp

Software Engineer at Cognizant

June 1, 2019 - November 1, 2022

Architected real-time fraud detection pipelines using Kafka, Spark Streaming, and UPI payment APIs, achieving <200 ms latency across 5M+ transactions while reducing fraud losses by 32%. Improved anomaly detection precision by 28% using XGBoost, feature engineering, and transaction-risk modeling, reducing false positives in payment screening workflows. Built adaptive risk-rule engines with object-oriented design and modular backend patterns, reducing fraud leakage by 30% while supporting regulatory audit requirements. Created AI-driven credit scoring models using alternative data and bureau integrations, increasing loan approval rates by 22% while lowering default exposure. Optimized ETL workflows with Airflow, AWS S3, and pipeline orchestration, reducing loan-processing turnaround time by 40% through faster KYC and verification flows. Delivered Tableau-based credit risk dashboards enabling stakeholders to reduce delinquency rates by 18% with faster portfolio insights.