Reeya Pimple | Research Engineer @ University of Washington

Reeya Pimple

Research Engineer @ University of Washington

Based in Washington/California

About

I am a dedicated Data Scientist with 3+ years of experience. My expertise lies in machine learning, data analysis, and visualization, skills I continue to refine as a Research Engineer at the University of Washington. Passionate about turning complex data into actionable insights, I strive to leverage data for innovative and insightful solutions.

Skills

Projects

Analyzing Amazon Product Data

Analyzing the Amazon products dataset by Exploratory Visual Analytics and Predictive Analytics, using Sagemaker to perform the analysis and AWS for data storage. Datasets Used: Amazon product co-purchasing network metadata

Predictive Modelling for a Retail Store

Implemented an XGBoost Algorithm to predict the future Profit based on past purchases, and conducted Market Basket Analysis using Apriori algorithm to recommend commonly co-purchased products. Also created a Tableau Dashboard to visualize the change in sales of various categories.

Identification of Cyber-Bullying using Natural Language Processing

Undergraduate Thesis: The framework consists of three main steps, which includes knowledge based sentiment analysis, whose result is then reinforced with machine learning based analysis. The resulting polarity is then aggregated with the polarity obtained from the emoticons for final segmentation.

Analyzing Impact of Mask-Mandates on Covid cases

Analyzing learn how the population of a specific region was impacted by the pandemic, not only in quantitative terms like number of cases, but also in qualitative terms like life standards. For the purpose of this analysis, we have chosen Jackson county from the state of Missouri.

Text Scrub Package in Python

Built a text cleaning package,TextScrub, for the following users: Analysts: Requiring quick data-cleaning functionalities, and who are not technically adept Data Scientists: Programmers wanting to clean web-scrapped data. Focus on experimenting with model-building instead of scrubbing

Experience

2023-2024

Research Engineer at UW

● Researching state-of-the-art Image Classification techniques using Deep Learning Framework Pytorch. ● Develop and implemented an Image Classification pipeline utilizing ResNet and VGG architecture using PyTorch. ● Applied Transfer Learning to improve accuracy of ResNet model to 80% and presented insights using Seaborn. ● Researching to make LLM (GPT) responses more resistant to disruptions, for real-world forecasting tasks.

2022-2023

Data Scientist at Zillow (Capstone)

● Led the creation of a Tableau Dashboard for Zillow, analyzing affordable rental listings in 25 U.S. cities. Defined Key Performance Indicators (KPIs) to support Zillow's goal of expanding income-restricted inventory. ● Implemented a landscape analysis to assess demand from users for the given cities, using Python.

2022-2022

Data Analyst Intern at UNDP

Global Center for Technology, Innovation and Sustainable Development ● Implemented a Data Imputation model to fill missing data for Small Island Developing States (SIDS) Data Platform. ● Built Correlation and Clustering analysis for 39 SIDS countries. ● Led a team of 6 UN Volunteers to create a Data Science online course for SIDS.

2019-2021

Data Scientist at PeAR Technologies

● Analyzed A/B testing results for new product features, demonstrating a 25% higher adoption rate among users in the treatment group, validating feature effectiveness, and influencing the product roadmap. ● Developed Predictive Analytics using Spark SQL on Databricks to extract, transform, and uncover insights from the raw data.

2018-2019

Analyst at JP Morgan Chase

● Developed benchmarking financial models and detailed company profiles for over 20 key clients covering IT, pharma, retail and oil & gas sectors. ● Implemented a Forecasting model in R, to predict the Working Capital requirements of clients. ● Automated the Forex Dashboard in Tableau for a dynamic and responsive visualization to track product performance for bankers and clients improving efficiency by 50%. ● Achievements: Among one of the highest rated new joiners at the year-end feedback cycle.

Education

2021-2023

Data Science at University of Washington

2014-2018

Computer Engineering at University of Mumbai

College Name: Dwarkadas J Sanghvi College of Engineering