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Hi, I'm Nehith Komaravolu, an AI/ML Engineer with 3+ years of hands-on experience designing and deploying machine learning models for risk analytics and fraud detection in large-scale financial systems. I excel in Python, SQL, Scikit-learn, XGBoost, AWS, and Azure, and I focus on real-time deployment, data pipeline automation, and performance monitoring. I thrive on translating complex data into actionable intelligence through scalable APIs, serverless architectures, and continuous retraining workflows. I enjoy collaborating with cross-functional teams to deliver high-impact AI solutions that optimize decision-making and operational efficiency.…Hi, I'm Nehith Komaravolu, an AI/ML Engineer with 3+ years of hands-on experience designing and deploying machine learning models for risk analytics and fraud detection in large-scale financial systems. I excel in Python, SQL, Scikit-learn, XGBoost, AWS, and Azure, and I focus on real-time deployment, data pipeline automation, and performance monitoring. I thrive on translating complex data into actionable intelligence through scalable APIs, serverless architectures, and continuous retraining workflows. I enjoy collaborating with cross-functional teams to deliver high-impact AI solutions that optimize decision-making and operational efficiency.

Nehith Komaravolu

AI Engineer, AI Developer, Data Scientist, +3

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Hi, I'm Nehith Komaravolu, an AI/ML Engineer with 3+ years of hands-on experience designing and deploying machine learning models for risk analytics and fraud detection in large-scale financial systems. I excel in Python, SQL, Scikit-learn, XGBoost, AWS, and Azure, and I focus on real-time deployment, data pipeline automation, and performance monitoring. I thrive on translating complex data into actionable intelligence through scalable APIs, serverless architectures, and continuous retraining workflows. I enjoy collaborating with cross-functional teams to deliver high-impact AI solutions that optimize decision-making and operational efficiency.…Hi, I'm Nehith Komaravolu, an AI/ML Engineer with 3+ years of hands-on experience designing and deploying machine learning models for risk analytics and fraud detection in large-scale financial systems. I excel in Python, SQL, Scikit-learn, XGBoost, AWS, and Azure, and I focus on real-time deployment, data pipeline automation, and performance monitoring. I thrive on translating complex data into actionable intelligence through scalable APIs, serverless architectures, and continuous retraining workflows. I enjoy collaborating with cross-functional teams to deliver high-impact AI solutions that optimize decision-making and operational efficiency.

Available to hire

Hi, I’m Nehith Komaravolu, an AI/ML Engineer with 3+ years of hands-on experience designing and deploying machine learning models for risk analytics and fraud detection in large-scale financial systems. I excel in Python, SQL, Scikit-learn, XGBoost, AWS, and Azure, and I focus on real-time deployment, data pipeline automation, and performance monitoring.

I thrive on translating complex data into actionable intelligence through scalable APIs, serverless architectures, and continuous retraining workflows. I enjoy collaborating with cross-functional teams to deliver high-impact AI solutions that optimize decision-making and operational efficiency.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Advanced

Work Experience

AI/ML Engineer at State Street

June 1, 2024 - Present

Designed and deployed end-to-end ML workflows for credit risk using Random Forest and XGBoost in AWS SageMaker; built data pipelines in SQL and Python to aggregate credit history, income, and macro indicators from internal systems and third-party sources. Implemented automated retraining with Apache Airflow, developed preprocessing for unstructured employment data, and integrated AI-driven risk scoring APIs for real-time underwriting insights. Visualized model outputs with Tableau and Power BI, and collaborated cross-functionally to ensure fairness and compliance with version control via Git/GitHub.

Machine Learning Engineer at Hexaware Technologies

July 1, 2020 - December 1, 2022

Curated structured and streaming data using MySQL, Python, and Apache Kafka for predictive modeling in credit risk and fraud detection. Engineered features (debt-to-income ratio, repayment delays, transaction frequency) with Pandas/NumPy and Scikit-learn pipelines. Built and fine-tuned ensemble models (XGBoost, LightGBM, CatBoost) with SMOTE and time-aware validation to handle class imbalance and drift. Developed explainable models with Statsmodels and Fairlearn for compliance; deployed real-time scoring APIs via Flask/FastAPI in Docker/Kubernetes (AKS); monitored latency and drift with Prometheus and Grafana; created Power BI dashboards. Automated retraining pipelines in Azure using Airflow DAGs and Azure Blob Storage; practiced robust MLOps with Git/Jenkins and reproducible workflows in Jupyter/PyCharm.