Purva Firodia
Machine Learning Engineer @Northern Trust
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WORK HISTORY
Machine Learning Engineer @Northern Trust
US
Designed, trained, and deployed fraud detection models (XGBoost, PyTorch, SQL feature engineering) on 100M+ transactions, reducing false positives by 22% and saving the bank $1.5M annually.• Developed time series forecasting pipelines (ARIMA, LSTM, Python, Airflow) to predict client cash flow and liquidity needs, improving forecast accuracy by 18%, which enhanced treasury planning decisions.• Built ETL pipelines in Snowflake + Airflow to process 50M+ daily transactions, optimizing SQL queries and cutting pipeline latency by 40%, achieving 99.9% reporting accuracy for compliance.• Automated Python + SQL-based anomaly detection scripts for high-value trades, reducing manual monitoring time by 35% and strengthening fraud risk controls.• Designed Power BI dashboards integrated with SQL backends to visualize portfolio risk, client segmentation, and anomalies, accelerating executive decision-making by 30%.• Integrated Salesforce APIs with ML risk models to push real-time fraud alerts into CRM workflows, enabling relationship managers to take proactive action and improving customer trust scores by 15%.• Collaborated with cross-functional teams (Risk, Treasury, IT) under Agile/Scrum, ensuring on-time delivery of 95% of ML projects while maintaining strict compliance and audit controls.
EDUCATION
University of Colorado Boulder
Master's degree
Savitribai Phule Pune University
Bachelor of Engineering - BE
ABOUT PURVA FIRODIA
I’m a Machine Learning Engineer and Data/Business Analyst with 3+ years of experience delivering AI/ML and analytics solutions across finance, SaaS, and enterprise platforms. My work bridges advanced machine learning with practical business insights—helping organizations reduce costs, improve efficiency, and make smarter decisions. I specialize in: Data Analytics & BI: SQL, Tableau, Power BI, and real-time dashboards that drive 15–25% improvements in efficiency, revenue, or decision-making. AI/ML Engineering: NLP, LLMs, computer vision, and time series forecasting with TensorFlow, PyTorch, and scikit-learn—achieving measurable outcomes like 22% fewer fraud false positives and $1.5M annual savings. Data Engineering & Cloud: ETL pipelines, Snowflake, Airflow, Apache Spark, and AWS (SageMaker, Lambda, Bedrock) for scalable, production-ready solutions. Business Impact: From fraud detection and churn reduction to AI-powered CRM integration (Salesforce), I focus on creating solutions that directly impact customer trust, revenue growth, and operational efficiency. Currently pursuing my Master’s in Management Information Systems at the University of Colorado Boulder, I combine technical expertise with business acumen to deliver data-driven solutions that matter. I’m open to opportunities as a Data Analyst, Business Analyst, Machine Learning Engineer, or Data Scientist, where I can apply my skills to solve complex problems and generate measurable business value.
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