I am a Data Engineer and Python Engineer with over 5 years of experience building data engineering, machine learning, and analytics solutions for banking and financial services organizations.
My background is centered on fraud detection, AML transaction monitoring, credit risk analytics, KYC workflows, and regulatory reporting, where I have helped improve operational efficiency and decision-making.
I have built both batch and real-time data pipelines using Python, PySpark, Apache Kafka, Apache Airflow, Snowflake, and dbt across AWS and Azure environments.
I also have hands-on experience with cloud-native deployment and orchestration tools such as Docker, Kubernetes, Red Hat OpenShift, and CI/CD pipelines, supporting production-grade analytics and ML systems.
In addition, I have worked across the full machine learning lifecycle, including feature engineering, model development, deployment, monitoring, and MLOps practices using MLflow, DVC, and related tooling.
I enjoy collaborating with engineering, risk, compliance, and operations teams to translate business requirements into scalable solutions, and I have also contributed to AI-powered compliance search applications using LangChain and OpenAI APIs.
Built real-time fraud detection data pipelines using Apache Kafka and PySpark Structured Streaming; modeled customer behavioral features in Snowflake using dbt; contributed to migrating legacy batch scoring workflows to event-driven services; automated CCAR stress-testing report generation; built a RAG-based compliance search tool; used MLflow and Evidently AI for model tracking and drift monitoring.
Developed and optimized PySpark AML transaction monitoring pipelines on Azure HDInsight; built feature engineering pipelines for fraud analytics; developed FastAPI microservices deployed on OpenShift and AKS; engineered Airflow DAGs for ingestion, validation, scoring, and SAR report generation; implemented data quality validation and reconciliation jobs; created Tableau dashboards.
Rebuilt the credit risk data mart in Snowflake using dbt and Airflow; wrote PySpark jobs on Azure HDInsight for AML transaction monitoring; containerized a retail credit scorecard pipeline and deployed it on AKS; exposed model predictions through FastAPI services; contributed to A/B testing and model governance documentation.
Built Python ETL pipelines to migrate transaction data from Oracle to PostgreSQL; developed NLP classifiers to route customer support tickets; automated financial reporting workflows; contributed to a KYC document verification module using OpenCV and Tesseract OCR; improved test coverage for Python data processing libraries.
M.S. in Information Technology & Project Management
Michigan
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