M.S. Business Analytics student at UMass Amherst (GPA: 4.0) with a background in AI & ML. Experienced in building predictive models, automating ETL pipelines and delivering executive ready dashboards. Skilled in Python, SQL, Power BI and Tableau - with a strong focus on turning complex data into clear, actionable business recommendations.
GPA: 4.0 · Coursework: Business Intelligence & Analytics, Statistical Analysis for Decision Making, Python for Business, Artificial Intelligence for Business, Data Management, Project Management, Data Visualization in Business, Machine Learning for Business, Cyber Security for Businesses.
GPA: 3.2 · Strong foundation in ML algorithms, deep learning and data structures. Awarded Silver Medal in NPTEL's "The Joy of Computing with Python" (IIT Madras) for excellence in programming and problem-solving.
Analyzed KPIs, budgets and participation metrics across 10+ campus initiatives supporting 500+ student participants annually. Collaborated with 15+ cross functional team members to streamline workflows, stakeholder coordination and operational tracking across 8+ large scale events. Developed data driven outreach and engagement strategies contributing to a 20% increase in student engagement and improved overall event participation.
Audited 5+ structured and unstructured datasets using Python and SQL, improving executive reporting reliability by 15%. Designed and deployed automated ETL pipelines that reduced analyst preprocessing time by 20%. Built 3 end to end ML models (House Price Prediction, Iris Classification, Resume Parser) achieving production ready benchmarks. Engineered a predictive pricing model using regression analysis that outperformed the baseline by 12% and delivered stakeholder ready dashboards translating model outputs into business recommendations.
Supported end-to-end recruitment activities including candidate sourcing, screening, interview scheduling, and applicant tracking. Collaborated with hiring managers to streamline recruitment workflows and improve candidate communication throughout the selection process. Strengthened stakeholder management and professional communication skills by engaging with prospective candidates and coordinating hiring activities across multiple roles.
Programming & Query Languages
BI & Visualization
Machine Learning & Analytics
Data Engineering
Cloud & Data
Certified in AI workloads, machine learning concepts, computer vision, natural language processing and conversational AI on Azure.
Fundamentals of Claude, prompt engineering, AI-assisted workflows and responsible AI practices.
Core AI concepts, frameworks, model capabilities, limitations and practical AI adoption strategies.
Data collection, cleaning, transformation, statistical analysis, visualization and data storytelling for business insights.
Foundations of Generative AI, prompt engineering, responsible AI and practical business applications.
Applied data visualization and business intelligence techniques to transform complex datasets into actionable insights and support decision making.
Performed data cleaning, analysis, visualization and storytelling to solve real world business challenges using data driven approaches.
Awarded for outstanding performance in programming fundamentals, computational thinking and problem solving.
Developed a novel semi-supervised ML framework for cybersecurity threat detection achieving 94.8% accuracy in identifying DDoS attacks in real time network traffic. The model significantly reduces false positives compared to traditional supervised approaches.
View PublicationLed end to end planning and execution of large scale student events - overseeing logistics, vendor coordination, volunteer management and program delivery for campus wide initiatives.
Managed creative direction for cultural and engagement events, developing promotional materials and coordinating design strategies to enhance student participation.
Led community outreach initiatives and coordinated social welfare programs, demonstrating organizational leadership and commitment to social impact.