Hi, I'm Saaim Khan
CS & DS | Data Analyst & Business Solutions Architect
I'm a Computer Science and Data Science student exploring the intersection of technology, business, and finance. I'm passionate about using data to solve real-world problems and build scalable solutions.
Programming
Python, TypeScript, Java, SQL
Data Analysis
NumPy, Pandas, Matplotlib, Seaborn
Communication
Public Speaking, Presentations, Team Leadership
Business Intelligence
Power BI, Excel, Data Visualization
Experience
Data Analytics Intern
Menarini Stemline, New York City, NY
- Led weekly SAP training sessions for 50+ users across time zones, improving system proficiency and cutting GR posting times by 25%.
- Developed SAP process documentation, streamlining onboarding and reducing system errors by ~30% for more accurate reporting.
- Automated SAP ticket tracking with Excel and Power BI, cutting manual reporting by 40% and improving real-time visibility for decision-making.
- Drove 20% adoption of SAP Mobile Start, leading a targeted engagement plan to increase usage.
Product Management Intern
Verge, New Jersey
- Developed and executed go-to-market strategies, defining target audiences and refining product-market fit (PMF) to drive adoption and engagement.
- Conducted in-depth competitor analysis, benchmarking features, pricing, and user experience to position Verge as a competitive player in the personal finance market.
- Researched and iterated on product-market fit, identifying core user needs and shaping the product roadmap to align with market demand and business objectives.
Projects
AI-powered platform that automates job applications using LLM technology and Python-based data processing.
- Implemented Python-based scripting to clean and preprocess resume data, ensuring optimized input for AI-powered automation
- Leveraged Vercel AI SDK and Stagehand to implement LLM-powered resume parsing directly in the browser, enabling faster, privacy-focused AI-driven job matching
- Developed a scalable backend in Next.js 13 (TypeScript), integrating with job boards for high-performance data retrieval and form population
Advanced financial analytics platform providing real-time stock data visualization and technical indicator analysis for informed investment decisions.
- Engineered an interactive stock analysis dashboard using Python, leveraging financial libraries like yfinance for real-time data retrieval and processing
- Implemented sophisticated technical indicators (MACD, RSI, Bollinger Bands) with NumPy for computational efficiency, enabling precise trend identification and trading signals
- Developed a comprehensive visualization system with Matplotlib and Pandas for multi-dimensional analysis of price movements, volume patterns, and correlation metrics
SAP Ticketing Analytics Dashboard
Automated Power BI dashboard replacing manual Excel reports to provide real-time insights for leadership on SAP ticketing data.
- Transformed SAP ticketing analytics by replacing manual Excel reports with an automated Power BI dashboard, providing real-time insights for leadership.
- Developed key KPIs—Tickets Opened, Tickets Closed, and Tickets by SAP Module—to improve IT performance tracking and resource allocation.
- Identified trends in ticket resolution, helping leadership proactively address inefficiencies and optimize support workflows.
Advanced statistical model leveraging R and machine learning to predict heart attack risk factors from clinical data with high accuracy.
- Developed a sophisticated predictive model using R's advanced statistical libraries (caret, tidyverse) to identify key cardiovascular risk factors from clinical datasets
- Implemented feature engineering and model optimization techniques to achieve 85%+ prediction accuracy, enabling early intervention opportunities
- Created comprehensive visualization dashboards with ggplot2 and shiny to present risk stratification and personalized health recommendations