Data Scientist Machine Learning

Shalagha “Shasha” Mundepi

628-***-**** ***********@*****.*** San Francisco, CA Github LinkedIn EDUCATION

Master of Science, Business Analytics - University of California, Davis San Francisco, CA Jun. 2024 Coursework: SQL, Data Management, Advanced Statistics, Big Data, Cloud Computing, Machine Learning Bachelor of Commerce (Economics Honors) & PG Diploma in Computer Applications- Panjab University India Jul. 2022 Coursework: Finance, Business Economics, Statistics, Marketing Management, Linear Algebra, Calculus PROFESSIONAL EXPERIENCE

Data Scientist - Qualcomm (UC Davis Practicum) Sep. 2023 - Jun. 2024

•Drove a projected $2.4M increase in annual revenue and elevated laptop selection accuracy by 37% by managing a team of 4 data scientists deploying a Random Forest model using Python (Scikit-learn) and SQL (Complex Joins, CTEs).

•Enhanced campaign targeting precision by 3x and improved conversion ratio by 5% through optimized digital marketing campaigns, leveraging rigorous A/B testing to identify loyalty, churn, and brand affinity across a 2M+ customer base in the United States.

•Saved 150+ man-hours per month by automating complex reporting processes with Excel (VBA macros, Pivot tables), reducing errors by 30% and speeding up report generation for 5 key business stakeholders.

•Elevated forecasted sales by $800K and uplifted customer satisfaction by 11% through customer analytics in conjoint and multivariate analysis. Data Analyst (Cloud Operations) - Accenture (Client: Carlsberg) Nov. 2021 - Jul. 2023

•Orchestrated a $1.7M+ revenue increase by leading a growth initiative that identified and expanded high-potential partnerships for the brewery business, leveraging data analysis in SQL to develop business cases for expansion across the Baltics (Europe).

•Reduced infrastructure costs by 32% through root cause analysis, enhancing operational efficiency for 7M+ data points, and positioning the company as a digital leader in the industry by leading the client’s IT transition from legacy systems to AWS.

•Optimized real-time data access for 50+ business users and expedited issue resolution related to delivery failures & increased on-time deliveries by 20% across 7+ business units by engineering a Looker dashboard with GCP analytics for real-time KPI monitoring.

•Boosted cloud infrastructure deployment efficiency by 22% and accelerated customer activation to 15 days by optimizing Carlsberg’s eCommerce onboarding process through A/B testing and data-driven enhancements, reducing setup time.

•Supervised cross functional teams of 6 data engineers to automate audit processes using Alteryx and Git for version control, enhancing efficiency by 50% and reducing audit cycle time from 6 weeks to 3 weeks, facilitating quicker compliance checks and faster issue resolution.

•Delivered $1.5M in annual cost savings and drove commercial velocity by automating cloud resource allocation with AWS CloudFormation. Financial Analyst Intern - Bank of India Sep. 2021 - Dec. 2021

•Safeguarded $300K in assets and reduced potential losses by 12% by developing a financial risk assessment model that identified and mitigated high-risk loan portfolios.

•Generated $20K in revenue and increased loan approvals by 5% by performing financial modeling and forecasting with ARIMA models and Time-Series Analysis in Python, identifying new customer segments with a <8% default rate through data mining techniques. PROJECT WORK

A/B Testing for Fast Food Marketing Mar. 2024

•Developed 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. Advanced Fine-Tuning of Llama 2 LLM for Enhanced AI Performance Oct. 2023 - Dec. 2023

• Revamped model parameters and augmented performance metrics by 50% through fine-tuning the Llama 2 Large Language Model on Vast.ai, leveraging Python and Hugging Face’s API in a cloud-based environment. Predictive Demand Forecasting for Supply Chain Optimization Sep. 2023

•Enhanced forecast accuracy by 30% and minimized stockouts by 20%, generating an anticipated annual savings of $250K by deploying ARIMA and XGBoost models for demand forecasting across 1,000+ SKUs. Automated Anti Money Laundering (AML) Detection System using Graph Analytics Nov. 2022

•Accelerated manual review processes by 70% and uncovered 500 additional fraudulent activities annually by engineering an automated AML detection system using Python, Neo4j, and machine learning models, including SVM and Gradient Boosting. SKILLS

Skills: Excel (VLOOKUP, Pivot Tables, Macros), SQL (CTEs, Window Functions, Complex Joins), Tableau, Power BI, Looker, Apache Spark, AWS QuickSight, Alteryx, JIRA, QlikView, SAP, Git, MS Office (Word, Outlook, PowerPoint), Agile Development Statistical Techniques: A/B Testing, Regression Analysis (Lasso, Ridge, Elastic Net, Logistic), Covariance and Correlation modeling, ANOVA, Principal Component Analysis, Elasticity Estimation, Conjoint Analysis, Multi-Armed Bandit Strategies, Causal Inference, Time- Series Analysis, Hypotheses Testing, Forecasting, Experimental Design (RCT), Bayesian Methods, Multivariate Analysis Machine Learning Techniques: Python (NumPy, Pandas, Scikit-learn, Matplotlib), Decision Trees, Random Forest, Support Vector Machines

(SVM), XGBoost, Neural Networks (Feedforward), Convolutional Neural Networks (CNN), Clustering, Anomaly Detection Specialties: Root Cause Analysis, Web Scraping, Data Wrangling & Modeling, Predictive Analytics, Data Storytelling, Value Realization, OKRs, Process Improvement, Project Execution, Cross-functional Collaboration, Growth Initiatives, Stakeholder Management Certifications: Google Data Analytics Certification, AWS Certified Cloud Practitioner, Tableau Desktop Specialist, Lean Six Sigma Green Belt Awards: Bronze Brilliance Award & Best Storytelling Award, University of California, Davis; Hackathon (Aggie Hacks)

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