Sayali Saraf

Experienced Data Engineer specializing in ETL development, data modeling, and SQL programming. Skilled in big data technologies (Hadoop, Spark) and cloud platforms (Databrick, Azure), building scalable and efficient data pipelines. Proficient in Python and Gen AI, with expertise in data visualization using Streamlit and Tableau. Experienced in CI/CD for seamless deployment and automation. Passionate about delivering high-performance data solutions for analytics and machine learning

• Credit Card Fraud Detection using Hybrid Ensemble Mo
• Task: Classify the fraudulent and legitimate transaction using Hybrid Ensemble Model
• Use Case: The model is trained on European credit card fraud dataset and credit card stimulation dataset
• Preprocessed using oversampling and covert highly imbalanced dataset into balanced dataset
• Hybrid Ensemble is trained on balanced dataset to predict the classification output by combining random forest and Adaboost
• Restaurant Review Prediction using Machine learning and NLP
• Task: Prediction and classification of restaurant reviews either “Good” or “bad” using Word Embedded and Machine Learning algorithm
• Use Case: Help researchers better understand to choose the better restaurant
• Preprocessed and covert text data into numerical by wordcount technique
• Machine learning algorithm include Logistic regression, Support vector machine, decision Tree
• Comparison all algorithm and choose better accuracy result and then predict the good and bad restaurant

• Published a paper entitled” Detection of Credit Card Fraud Using a Hybrid Ensemble Model.” In IJACSA (www.IJACSA.thesai.org) ISSN UGC Approved (Journal No:0130953) Published in Vol. 13, No. 9, 2022| Date of Publication:2022-09-09.

• SQL Beginner to Advanced Level - Data Analytics
• DevOps Beginners to Advanced with Projects

• Bronze Award at Mercedes Benz Research & Development

I hereby declare that the above particular are true to the best of my Knowledge and belief .

Place : Bangalore