AI Engineer/ Senior Data Scientist at Travelport

Designed and deployed Generative AI solutions with Retrieval-Augmented Generation (RAG) using LangChain, FAISS, and Hugging Face embeddings to enable enterprise knowledge search across travel documentation, APIs, and support resources. Built LLM-powered assistants for travel queries and itinerary recommendations, improving support response efficiency. Developed and optimized ML models (XGBoost, Random Forest, SVM) to predict customer behavior and booking trends, achieving 25-30% improvement in prediction accuracy. Engineered scalable data pipelines using PySpark, SQL, and Airflow; implemented semantic search with vector embeddings; built real-time inference APIs; and established MLOps using MLflow, Docker, Kubernetes, and CI/CD. Performed model explainability with SHAP and monitoring; created dashboards with Tableau/Power BI; integrated geospatial analytics with GeoPandas.

Senior Data Scientist / AI Engineer (Machine Learning & Generative AI) at First

Deployed ML and AI generation technologies to support financial analytics, credit risk, and customer intelligence using Python and Spark. Developed prediction models (XGBoost, Random Forest, Gradient Boosting) to analyze borrower behavior and loan performance, achieving 20-25% accuracy improvements. Built RAG pipelines with LangChain, FAISS, and transformer embeddings for document search and generation. Implemented NLP pipelines using BERT and Hugging Face Transformers to analyze large volumes of unstructured financial data. Engineered scalable ETL and feature engineering pipelines using PySpark, SQL, and Airflow for transaction data. Designed semantic search systems to improve document retrieval and knowledge management. Developed time series forecasting models (ARIMA, Prophet, LSTM) for agricultural loan demand and market trends. Implemented MLOps using MLflow, Docker, CI/CD for production deployment. Performed EDA and visualizations with Tableau/Power BI; ensured model explainabilit

Data Scientist at Equifax

Developed data models and insights guiding operations and strategy. Used SQL and Python to study large datasets; contributed to feature engineering, data preparation, and model validation. Automated reporting tasks reducing manual work by over 30%, improved data quality, and supported cloud migrations. Worked with business partners to translate needs into data solutions, performed exploratory data analysis to identify patterns and insights, and built dashboards with Tableau and Power BI. Maintained data quality checks and documentation; provided analytics support across teams.

Junior Data Scientist at Cummins

Analyzed structured enterprise data to provide actionable insights and performance metrics for management reporting. Designed SQL queries, views, and stored procedures for dashboards and executive reports. Assisted in KPI development for sales, operations, and finance; supported data preparation, model development, and validation. Performed data cleaning, normalization, and transformation; developed dashboards and visualizations; supported data integration and data quality checks. Documented data definitions and business rules; contributed to automation of repetitive reports; participated in UAT and production validation.