Data Scientist

ARCHITA VASUKI

*****************@*****.*** +1-206-***-**** linkedin.com/in/architavasuki/ bit.ly/architavasuki Seattle, WA EDUCATION

University of Washington – Michael G. Foster School of Business Seattle, WA Master’s in Business Analytics Jun 2023 – Jun 2024 Coursework: Marketing & Customer Analytics, Supply Chain & Operations, Finance, Pricing Analytics, Competitive Strategy BNM Institute of Technology (Affiliated to VTU) Bengaluru, Karnataka, India BE Computer Science and Engineering Aug 2016 - Aug 2020 Coursework: Python, Machine Learning, Operations Research, Database Management, Objected Oriented Programming WORK EXPERIENCE

TheMathCompany Pvt. Ltd. Bengaluru, Karnataka, India Global data analytics and data engineering, business consulting and services firm Associate Data Scientist Jul 2021 - Apr 2023

• Engineered a successful price elasticity dashboard for a leading CPG company using Linear Regression, resulting in 20M USD revenue benefit; garnered ‘Simplified Innovation Award’ from the CEO [Python, SQL, Azure, Snowflake]

• Deployed Random Forest Classifier as a recommendation system for customers purchasing new vehicles, boosting up- selling of accessories by 0.5M USD revenue [Python, SQL, AWS]

• Spearheaded a team of 5 analysts to build QlikSense dashboards, propelling 2x adoption of marketing campaign metrics; received 'Appreciation Award' for taking dashboarding initiative [SQL, Data Modeling] Data Scientist Jul 2020 - Jun 2021

• Constructed predictive models using Logistic Regression and Naïve Bayes for a leading automobile client, identifying loyal, churn, and brand affinity for 2M customers, improving campaign targeting by 2x, generating 2.3M USD profit

• Operationalized an end-to-end framework to predict customers re-purchasing vehicles within the same year using Logistic Regression, contributing to 5% increase in profit margins [Python, SQL, Git]

• Devised a Multi-touch Attribution model for a world leader in Hospitality Education, securing a 1-year contract and 1M USD revenue growth

• Optimized existing code by establishing ETL pipelines, streamlining and reducing run-time by 87.5%, saving the client 20 man-hours per week [SQL, Presto]

• Led a team of 3 to construct K-Means customer segmentation for an American entertainment company, enabling the marketing team to plan campaigns better, elevating conversion ratio by 5% [Python, SQL, Git, Azure] SKILLSET

• Machine Learning: Exploratory, Predictive, Statistical Analysis, Classification, Regression, Decision Trees, Time Series Forecasting, Clustering, Neural Networks, User Segmentation, Hypothesis & A/B Testing, Marketing Personalization, NLP

• Programming Languages: Python (Numpy, Pandas, Scikit-learn, Pytorch, PySpark, Flask), SQL, R, HTML, CSS

• Tools: MS Excel, Dialogflow, LLMs, GIT, API, MS Office Suite, Google Suite

• Business Intelligence: KPI, Report Generation, Tableau, PowerBI, QlikSense

• Data Engineering: Extract Transform Load (ETL), Snowflake, AWS (S3, Sagemaker), Azure (ADO, ML Studio), Airflow PROJECTS

A/B Testing for Fast Food Marketing Mar 2024

• Designed and executed A/B test for fast food marketing, identifying two Promotions (Collectibles and Loyalty Programs) as statistically significant sales drivers (vs. Societal Marketing Promotion) using Python Difference in Difference Analysis for Paid Search Advertisement Jan 2024

• Leveraged Difference-in-Difference analysis and Linear Regression to quantify a potential 60% ROI decline in Google paid search campaigns, based on a comparative analysis of Google and Bing traffic data using R Optimization of Paid Search Data for Hotel Bookings Dec 2023

• Employed a Semi-log model with carryover effects to quantify the impact of keywords on CTR and utilized decision tree modeling, resulting in a 15% improvement in reservation predictions Factory Profit Maximization Jan 2022

• Maximized factory profit by employing a Genetic Algorithm to optimize product quantities and weights, enhancing overall profitability [github.com/architavasuki/genetic_algorithms] Student GPA Predictor Jan 2020 - May 2020

• Consolidated 50K student records from 10 disparate datasets through extensive Exploratory Data Analysis and pre- processing using Python

• Delivered 80% accuracy predicting student GPA via lasso regression to identify at-risk students which was deployed using Flask framework, HTML and CSS

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