Parth Vadera Email & Phone Number

Sunnyvale, CA, US

Los Angeles, California, US

Designed and implemented risk strategy architecture (block, trust, media network, and suspicious user mining) along with feature store and data pipelines from initial concept through to production, streamlined development processes, and led the recruitment and mentoring of new team members, significantly boosting team cohesion and knowledge.

San Francisco, California, US

• Tech lead for developing global (America, Asia, Europe) forecasting capability at product level leveraged by planners and utilized as an input for other projects (Replenishment, Product Assortments, Pricing). Improved.
• Developed propensity models for Loyalty using wide and deep neural network model to address data sparsity (embeddings) and improved redemption rate across the board by 12 points YoY. Technologies Used: Tensorflow 2.
• Refactored email targeting approach to account for the recent apple privacy updates which reduced the impact of this update on revenue/user.
• Built a traffic forecasting engine to predict foot traffic at brick and mortar stores post reopening after covid shutdown for labor allocation and financial budgeting. Technologies Used: Python, XGBoost, Random Forest.
• Developed fit finder recommendation engine for similar products using embeddings from convolutional neural networks (Resnet50, Inception). Leveraged these embeddings to address cold start problem for forecasting sales.
• Built a what-if simulator tool to analyze the effects of changes in promotion price to overall sales for Levi’s brick and mortar business using probabilistic forecasting approach. Technologies Used: Python, DeepAR

Boston, Massachusetts, US

Implemented attribution model to measure the impact of TV Ads on web traffic using synthetic control method, BSTS, and Long-Short Term Memory (LSTM). Technologies Used: R, Python, KerasDeveloped automation tool for exploratory data analysis of 3rd party data and successfully tested on Rentrak and comScore. Technologies Used: PySpark, AWS EC2

Boston, MA, US

Collaborated with Medical records data engineers from U.S. Department of Veterans Affairs to build generative classification models (bayesian belief network) in order to predict and understand relationship between the risk factors and mental health in US Veterans. Technologies Used: R (bnlearn, randomForest, kernlab, ggplot2) & SQLLed a team of engineers.

Ahmedabad, Gujarat, IN

Developed an optimized targeted marketing model for an e-commerce website selling traditional apparel using customer segmentation, predictive modeling and A/B testing. Technologies Used: R (caret, OAuth2.0) & Google Analytics.Developed a forecasting model to predict the number of daily visitors on e-commerce websites using Holt-Winters smoothing.Assisted.

Master Of Science, Operations Research

B.Tech, Information And Communication Technology

Ssc And Hsc, Life.