Anish Amol Gaware

Master's student in data science and artificial intelligence at SRH Heidelberg University, holding a bachelor's degree in information technology. Possesses strong hands-on experience in data engineering, web scraping, and machine learning. Actively seeking working student or internship opportunities to apply technical skills in real-world projects.

https://www.linkedin.com/in/anish-gaware-4a10a8223

• SAS Visual Analytics 1 for SAS Viya: Basics
• SAS Visual Analytics 2 for SAS Viya: Advanced
• AWS Academy Graduate - Cloud Foundations
• AWS Academy Graduate - Cloud Architecting
• RDBMS PostgreSQL Indian Institute of Technology, Bombay

• Campus Ambassador- Pregrad, 2023-07-01, 2023-08-01, Promoting and selling Pregrad Courses to College Students all over Pune.
• Football Coordinator- College Sports Committee, 2023-24, Hosted and directed the Sports Committee and the Sports Activities in the college.

• Fitness
• Football
• Biking

1. AI Fitness Coach (Final Year Project)   1st August,2024-9thJune,2025

· Developed an AI based Fitness Web app.

· The app contains 2 main functionalities: Diet Recommendation System and Real time moments detection (Open CV).

· Developed the Diet Recommendation System in Javascript using Fitness Sciences logic.

· Realtime moment detection is done in python using Open CV and Media-Pipe.

2. SAS Data Visualization and Electoral Analysis (Germany)

· Designed and analyzed a synthetic dataset to study how socio-economic and demographic factors across Germany’s 16 federal states influence political party vote shares.

· Applied regression analysis to identify statistically significant drivers of vote shifts.

· Created scatter plots, correlation matrices, and geospatial (geo) maps to visualize regional voting patterns.

· Interpreted correlations between demographic variables and electoral outcomes to highlight high-impact regions and voter groups.

· Focused on data storytelling and visual analytics to support evidence-based conclusions.

3. Data Engineering Project (Real-estate Consultancy)

· Analyzed the website OnTheMarket data structures to identify relevant business features and designed end-to-end data extraction workflows.

· Built and enhanced web scraping and parsing scripts to handle dynamic content, inconsistent formats, and missing values across multiple sources.

· Performed data cleaning, deduplication, and column normalization to generate a high-quality, analysis-ready CSV dataset.

· Created business-focused analytical queries to support trend analysis, performance monitoring, and data-driven decision-making.

4. HushHush Recruiter - AI Powered hiring and  coding assessment platform

· Scraped candidate data from Stack Overflow and GitHub and selected relevant technical performance features.

· Performed feature engineering including scaling, normalization, and data transformations to enhance model performance.

· Applied clustering techniques and evaluated them using metrics such as Silhouette Score and Davies–Bouldin Index before selecting K-Means as the optimal model.

· Used cluster-generated labels as target variables for supervised learning.

· Trained and compared multiple regression algorithms; after visualization and evaluation of performance metrics, selected Logistic Regression for final ranking and prediction.

· Generated candidate scores from the trained model to rank and shortlist top-performing candidates.

· Developed a coding assessment platform from the hiring manager’s perspective, allowing managers to send secure test links via email.

· Enabled candidates to solve coding problems online, submit solutions, and automatically store results in a centralized dashboard for hiring decisions.