Resume

1. Tanaya Kavathekar
202.290.5772 ♦ Washington DC ♦ tanaya_10@gwu.edu ♦ github.com/Tann10 ♦ Linkedin.com/in/tanayakavathekar
EDUCATION
The George Washington University, Washington, DC Anticipated May 2021
Master of Science, Data Science
Related coursework: Statistical Analysis, Multivariate Analysis, Quantitative Modeling Techniques
University of Pune, Pune, India May 2016
Bachelors in Engineering, Computer Engineering graduated with Distinction
TECHNICAL SKILLS
Programming: Python, R, PySpark, Hive, SQL, Django, Shell, Unit Testing, Java, C, C++
Statistical Techniques: Time Series Analysis and Forecasting (ARIMA, ETS), Regression and Classification - Linear models
(Lasso, Ridge, Logistic), Non-Linear Models (GAM, MARS), Tree-Based Ensemble Models (Random Forest, Gradient
Boosting), Clustering (Time-series, K means)
Software: Excel, Docker, Git, Jenkins, JIRA, PowerBI, Microsoft Azure
PROFFESIONAL EXPERIENCE
Mu Sigma Business Solutions Pvt. Ltd., Bangalore, India Sep 2016 – July 2019
Decision Scientist
Key Accomplishments:
 Made data driven decisions for Fortune 500 clients across Technology, Retail, and CPG verticals by leveraging big
data to analyse and synthesize values and built scalable algorithms
 Received 3 sport awards for creative problem-solving ability, independently working on multiple APIs, showing
thought leadership and diverse technical capability
 Conducted classroom sessions and evaluated new recruits on problem-solving ability, building solutions and
coding standards
Key Projects:
Fortune 100, US-based Manufacturer, Supply Chain & Data Science Team
Demand Forecast
 Achieved a 15% improvement in case fill rate for the supply chain division by improving accuracy of demand
forecast by a factor of 8% , by building ensemble time-series models
 Worked on data engineering task to pull ~2TB (10 years) data from variety of sources using azure data factory and
data lake
Fortune 200, UK-based Retail Chain, Data Science & Technology Team
Sales Forecast Engine
 Increased the forecast accuracy of sales value and volume by 5.6% consumed by Finance Team, benchmarked
against the best legacy system, by implementing ARIMA with a customized seasonal adjustment
 Employed parallel processing for model building, scoring, and forecasting for ~2500 stores and ~3600 product
groups constituting ~1 TB of data using Hadoop and PySpark technology
Sales Forecast Diagnostic Engine
 Improved sales forecast accuracy by 2.4%, by building a diagnosis module using stepwise regression to analyse the
deviation between a forecast and its corresponding actual
Demand Transfer on the Delisting of Products
 Lifted profit margin by 1.3% by predicting demand transfers for delisting products, by building a union of ensemble
models (time-series + random forest) and business heuristics
Middleware API Development
 Integrated complex product hierarchy filters in multiple web-based tools, used for reporting, ranging, and pricing
across organization, by building modularized APIs
 Developed a multi-layer ADFS authentication framework using Django to enable privacy-controlled
authorization across views
LEADERSHIP & EXTRACURRICULAR
International Student Association Sep-2019- Present
Associate Director of Graduate Affairs
PUBLICATIONS
 Cyber Times International Journal of Technology and Management, Creating Cloud for Virtual Lab (Research
paper), Nov. 2015
 International Advanced Research Journal in Science, Engineering, and Technology, Creating Cloud for Virtual Lab
(Implementation paper), May 2016