Data Analytics & ML Engineer with Business Analytics MS

Sadhvi Patil

617-***-**** ***********@*****.*** LinkedIn

Education

University of Massachusetts Boston Boston, MA

Master of Science in Business Analytics, GPA: 4/4 Sep’24 – May’26 PES University Bengaluru, India

Bachelor of Technology in Computer Science Engineering, Data Science specialization Aug’16 – May’20 Experience

Tech Goes Home Boston, MA

Data Analyst Intern Jun’25 – Dec’25

• Increased reporting accuracy by 30% and reduced manual processing time by 40% by cleaning and analyzing program data using SQL and Excel Macros.

• Improved software license management by building automated Salesforce renewal-alert workflows, reducing lapse risk and overspending.

• Boosted follow-up efficiency by 45% by building Salesforce dashboards and reports for ongoing KPI tracking and year-over-year performance comparison.

• Developed 6 FormAssembly pre- and post-course learner forms with Salesforce connectors for real-time data capture, enabling analysis of learner knowledge gaps and learning outcomes to inform course improvements.

• Created interactive Tableau dashboards summarizing learner trends such as enrollment, course types, age groups, satisfaction, and return intentions to evaluate overall program effectiveness. Pramata Knowledge Solutions Bengaluru, India

Data Scientist - Operations Aug’20 – Dec’23

• Engineered code for complex data patterns, directly enhancing script performance by 25% and improving data delivery speeds, which ensured faster turnaround for 20+ clients.

• Piloted data-driven product improvements by translating user feedback into actionable requirements, leading to a 15% improvement in user satisfaction scores and a higher adoption rate for key features.

• Led automation initiatives for 20+ clients and strengthened QA and data validation workflows, accelerating delivery timelines by 50%.

Projects

End-to-End Data Engineering & ML Project (Best Buy Dataset) UMASS, Boston Sep’25 – Dec’25

• Architected end-to-end analytics pipeline by web-scraping Best Buy laptop data using Selenium, cleaning datasets with Pandas, and designing SQLite database for scalable analysis of 550 data points.

• Trained ML models (Decision Tree, Text Analytics, Comparative Analysis) using scikit-learn to identify pricing drivers and segment laptops by performance tier, identifying 6 key pricing drivers and product performance segments.

Data Warehousing and Visualization Project UMASS, Boston Sep’24 – Dec’25

• Consolidated fragmented student data from 10+ sources into a centralized database by creating ETL pipelines, enhancing data consistency and reporting efficiency.

• Constructed multidimensional data cubes in Visual Studio and created insight-driven Excel visualizations, enabling 30% faster analysis of enrollment trends and improving data-driven decision-making by 15%. Spotify Song Popularity Prediction UMASS, Boston Sep’25 – Dec’25

• Conducted EDA on Spotify audio features from a dataset of 170,653 rows, identifying release year and key sound characteristics as strongest predictors using decision tree and random forest models.

• Trained and evaluated Decision Tree and Random Forest models using scikit-learn, achieving 87% classification accuracy and R = 0.80 regression performance on Spotify popularity predictions. Skills

Technical: SQL, Salesforce, Python, Macros, Jenkins,PowerBI, Tableau, Supply Chain Management, FormAssembly, MS Excel, AWS,Business Models, Data Mining, Marketing Analysis,Business Intelligence, ERP Project Management: Jira, Confluence, Asana, Rippling

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