Suhas Kolekar

I am an entry-level Data Scientist with a focus on solving complex business problems through machine learning, statistical rigor, and scalable data pipelines. My experience spans fraud analytics, recommendation systems, and experimentation, with a specific interest in navigating real-world constraints and trade-offs. My work at IDBI Intech Ltd. involves analyzing large-scale digital payment data to detect fraud patterns and behavioral anomalies. I specialize in designing risk indicators that balance high fraud recall with investigation capacity, ensuring that high-risk transactions are prioritized effectively. 𝐀𝐂𝐇𝐈𝐄𝐕𝐄𝐌𝐄𝐍𝐓𝐒: 𝐀𝐥𝐥 𝐈𝐧𝐝𝐢𝐚 𝐑𝐚𝐧𝐤 202 in the C-DAC PRE-CAT entrance examination. 𝐂𝐨𝐫𝐞 𝐂𝐨𝐦𝐩𝐞𝐭𝐞𝐧𝐜𝐢𝐞𝐬: 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: Classification, Regression, Feature Engineering, and Imbalanced Data Handling. 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 & 𝐒𝐐𝐋: Advanced SQL (CTEs, Window Functions), Python (Pandas, Scikit-learn), and End-to-End Analytics Workflows. 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬 & 𝐄𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧: A/B Testing, Hypothesis Testing, Power Analysis, and Confidence Intervals. 𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐢𝐨𝐧 & 𝐄𝐱𝐩𝐥𝐚𝐢𝐧𝐚𝐛𝐢𝐥𝐢𝐭𝐲: ROC-AUC, Precision-Recall, NDCG@K, and SHAP. 𝐓𝐨𝐨𝐥𝐬: Git, Docker, FastAPI, and AWS (EC2, S3). 𝐊𝐞𝐲 𝐏𝐫𝐨𝐣𝐞𝐜𝐭𝐬: 𝐄𝐧𝐝-𝐭𝐨-𝐄𝐧𝐝 𝐅𝐫𝐚𝐮𝐝 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠 𝐏𝐞𝐫𝐬𝐨𝐧𝐚𝐥𝐢𝐳𝐞𝐝 𝐑𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐚𝐭𝐢𝐨𝐧 𝐒𝐲𝐬𝐭𝐞𝐦 𝐄𝐱𝐩𝐞𝐫𝐢𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐅𝐫𝐚𝐦𝐞𝐰𝐨𝐫𝐤 I value clarity, measurable impact, and strong fundamentals. I am currently seeking full-time opportunities as a 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭, 𝐏𝐫𝐨𝐝𝐮𝐜𝐭/𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐭, or 𝐑𝐢𝐬𝐤/𝐅𝐫𝐚𝐮𝐝 𝐀𝐧𝐚𝐥𝐲𝐬𝐭.