Nov 2021 – Jan 2023 · 1 yr 2 mos · Remote

• Executed Price Optimization Modeling utilizing Naïve Bayes, Random Forest, Support Vector Machines, and Logistic Regression algorithms, achieving a 90% accuracy rate in forecasting market trends, optimizing markdown prices for products which lead to a significant $1M cost savings in inventory management.
• Collaborated with the Google team to implement and showcase Vertex AI, an upcoming feature in Google Cloud Platform, to integrate advanced machine learning models to enhance model performance metrics, achieving a 20% reduction in model training time and 15% improvement in prediction accuracy.
• Developed and deployed a virtual fitting room solution by engineering real-time data integration from webcams and mobile devices, enabling instant virtual try on experiences before purchasing, resulting in a 20% decrease in return rates through enhanced visualization accuracy and increased user engagement.
• Implemented advanced computer vision algorithms for body pose estimation and garment segmentation, to simulate garment fit on user images and improve garment realism & fitting accuracy, resulting in a 15% increase in customer satisfaction scores.
• Utilized TensorFlow and OpenCV to develop and fine-tune deep learning models for garment overlay and adjustment, in order to effectively manage and process extensive datasets of clothing images and SKUs, optimizing model performance by 20% for diverse clothing styles and body types.
• Leveraged clustering techniques to target customers by analyzing their historical, demographic, and behavioral data to implement personalized marketing strategies, resulting in a 30% revenue increase and business growth.

Jun 2021 – Nov 2021 · 5 mos

• Analyzed data using Python and SQL from 25,000 monthly active users and used outputs to guide marketing and product strategies, resulting in an 2x increase in average user engagement time and 30% decrease in drop off rate.
• Utilized advanced data analysis techniques such as Random Forest, Support Vector Machines (SVM), Naïve Bayes, Gradient Boosting Machines (GBM) for classification, regression, clustering, and anomaly detection, in order to streamline the ADP US Payroll system and contribute to a 15% reduction in payroll processing time.
• Conducted 15 thorough code reviews for 2 Sprints monthly, to ensure robust and efficient software development practices, resulting in enhanced code quality and error reduction in production by 30%.
• Effectively used boxplots and Pandas functions to handle outliers and missing values in the ADP US Payroll System, to ensure data quality and reliability, contributing to a 70% accuracy in payroll processing and increasing operational efficiency by 30%.

Jun 2018 – Jul 2021 · 3 yrs 1 mo

• Sumtotal is the leading provider of payroll and Benefit Management solutions. Played a key roll in Designing powerful, flexible solutions.

Nov 2014 – May 2018 · 3 yrs 6 mos

• Developed predictive models using logistic regression, resulting in a 50% increase in portfolio optimization.
• Analyzed 1TB in datasets using Python and SQL to identify trends and provide insights for asset allocation and risk management, reducing portfolio risk by 20%.
• Performed ETL processes in data cleaning, data modeling, data mining, and report sharing using Tableau, reducing turnaround time by at least 90% to meet the SLA’s standards.
• Designed and maintained Tableau dashboards to evaluate and track real time performance monitoring and reporting of the application.
• Developed and implemented forward-looking financial models, product profitability metrics, and 2 ad-hoc analyses monthly, to improve financial performance.
• Broadridge is the leading provider of investor communications and technology driven solutions for wealth management, asset management and capital markets firms.
• Developed applications for Annual General Meeting (AGM), inverstor communications.