PROFESSIONAL EXPERIENCE
Lead Data Scientist Mastercard | March 2022 – Oct 2025
- Architected and deployed distributed ML pipelines on AWS supporting real-time fraud detection processing 143+ billion transactions annually through Decision Intelligence Pro system, achieving
20-300% improvement in fraud detection rates and 85% reduction in false positives through advanced algorithm development and feature engineering
- Implemented Hugging Face Transformers for generative AI fraud detection scanning 1 trillion data points in under 50 milliseconds, reducing manual investigation time by 60% while maintaining regulatory compliance.
- Fine-tuned large language models (LLMs) on transaction narratives using advanced natural language processing and statistical analysis, improving conversation summary accuracy by 45% and enabling data storytelling for executive stakeholders.
- Led cross-functional team of 12+ data scientists in designing, building, and testing computer vision engineering solutions for merchant verification, contributing to $118 billion annual fraud prevention savings through advanced feature engineering and transfer learning techniques.
- Optimized reinforcement learning algorithms in cloud computing environments, reducing system latency by 25% and improving recommendation accuracy by 18% through sophisticated algorithm development and hyperparameter tuning.
- Designed A/B testing processes and analytics dashboards using statistical software and hypothesis testing methodologies, driving data-informed business decisions and enhancing marketing targeting effectiveness.
- Developed data architecture supporting big data analytics infrastructure with comprehensive data security measures, ensuring GDPR compliance and data transformation processes for global payment systems.
- Integrated MLOps pipelines with Kubeflow and Docker, reducing operational costs through automated data lifecycle management and implementing data profiling techniques for quality assurance.
- Applied time series analysis and predictive modeling techniques for transaction forecasting achieving 95% accuracy in fraud pattern prediction and enabling proactive threat mitigation strategies.
- Built clinical NLP pipelines for medical chart processing: sectioning, de-identification, entity detection (problems, meds, procedures), and ICD-10/CPT suggestion with human-in-the-loop review,
improving coder throughput by 32% and reducing DRG upcoding risk alerts by 18%.
- Deployed PySpark-based RCM anomaly detection (payment accuracy/smart reconciliation) over
1B+ claim lines, cutting denial write-offs by 6.4% and accelerating cash posting by 19 hours on average.work.
- Created medical image triage models (X-ray/ultrasound) with MONAI and U-Net variants;
prioritized review queues and reduced average turnaround time by 21%.
Senior Data Scientist General Motors | June 2021 – Dec 2021
- Delivered predictive maintenance models using time series analysis and statistical analysis,
increasing anomaly detection accuracy by 20% across 1,200+ daily vehicle production lines through multi-billion NVIDIA partnership.
- Implemented computer vision engineering solutions for quality inspection automation, reducing processing time by 30% and achieving $7.4M annual cost savings through advanced algorithm development.
- Deployed reinforcement learning optimization for digital twin manufacturing simulations using
NVIDIA Omniverse platform, improving manufacturing efficiency by 17% with zero safety incidents.
- Designed data architecture for connected vehicle platforms supporting big data analytics on 25K+
sensors, enabling predictive analytics for autonomous driving systems development.
- Applied feature engineering techniques to battery management systems data, enhancing electric vehicle performance optimization by 15% through sophisticated data transformation processes.
- Integrated cloud computing resources (AWS, Azure) for scalable data processing of automotive IoT data, implementing comprehensive data security frameworks for connected vehicle platforms.
- Utilized statistical software and data visualization tools to create executive dashboards, enabling data storytelling for C-suite decision-making regarding electric vehicle expansion to 12 models by 2026
Lead Data Scientist Hypergiant | January 2019 – December 2020
- Designed patented semantic segmentation models for defense and space applications, securing $61
million U.S. Air Force JERIC2O contract for Joint All-Domain Command and Control systems
- Implemented reinforcement learning algorithms for autonomous satellite operations, achieving 35%
mission efficiency improvement and 100% mission success rate for NASA, USAF, and Space Force clients.
- Developed computer vision engineering solutions for satellite imagery analysis using advanced CNN architectures, accelerating target identification workflows by 35% through sophisticated feature engineering.
- Implemented feature engineering techniques for defense sensor data analysis supporting $950
million Department of Defense IDIQ contract awards and multi-level security clearance systems.
- Integrated AI into astronaut equipment and OCR tools using natural language processing and statistical analysis, enhancing safety protocols and operational efficiency for space missions.
- Built scalable AI prototypes using Kubeflow and distributed computing technologies on cloud platforms, implementing comprehensive data security measures meeting DoD STIG requirements.
- Applied time series analysis and predictive modeling to satellite constellation management, reducing ground-station handover latency by 28% through advanced algorithm development.
AI/DL Data Scientist
Dell EMC | November 2017 – December 2018
- Led ML system design on big data infrastructure using Ready Solutions for AI, achieving 2.9x performance improvement over competitors and reducing AI deployment time by 6-12 months for
Fortune 500 enterprises.
- Implemented automated 5-click data science workspace provisioning using Jupyter notebooks and statistical software, boosting data scientist productivity by 30% through streamlined data lifecycle management.
- Optimized deep learning model training performance using mixed-precision techniques and advanced algorithm development, improving GPU utilization from 68% to 92% and reducing energy costs by 25%.
- Designed data architecture for enterprise AI democratization supporting cloud computing platforms
(AWS, Azure), enabling comprehensive data transformation and feature engineering workflows.
- Applied statistical analysis and hypothesis testing methodologies to validate model performance,
ensuring data quality assurance and implementing data profiling techniques for enterprise datasets.
- Integrated MLOps pipelines with comprehensive data security frameworks, enabling scalable deployment of machine learning models across diverse enterprise environments while maintaining data governance standards.
Data Scientist/Co-founder
ITSolidServices LLC | February 2014 – October 2017
- Developed AI-powered medical app 'Bluepad' using computer vision engineering and machine learning, achieving 95% diagnostic accuracy on mobile devices with HIPAA-compliant data architecture.
- Designed comprehensive data security and transformation infrastructure for healthcare clients,
implementing advanced encryption and data governance frameworks passing zero critical audit findings.
- Applied statistical analysis and feature engineering to clinical datasets, identifying key patterns and opportunities for predictive healthcare analytics and personalized treatment recommendations.
- Delivered AI training workshops for 120+ medical professionals, increasing healthcare AI adoption rates by 45% through effective data storytelling and technical documentation.
- Implemented natural language processing solutions for electronic health records, reducing provider documentation time by 25% through automated data annotation and algorithm development.
