VIMAL NAKRANI
Phone: 832-***-****
LinkedIn: www.linkedin.com/in/vimalnakrani08 E-mail: **************@*****.*** A Data Enthusiast with two years of experience in delivering meaningful insights for data using Machine Learning Models and Big Data Technologies.
EDUCATION
University of Houston Clear Lake August 2017- May 2019 MS in Computer Science
Mumbai University, Mumbai, India August 2013- May 2017 BE in Information Technology
Analytical Programs: SQL, Python, R, Power BI, Tableau, Git, Apache Spark, Hive, Hadoop, MapReduce Experience with: Regression, Classification, Cluster Analysis, Time Series, Neural Network models, Sentimental Analysis, Exploratory Data Analysis
Tools and Libraries: NumPy, Pandas, SciPy, Scikit-learn, TensorFlow, Seaborn, Matplotlib, Keras, Spacy, NLTK, MLlib PROFESSIONAL EXPERIENCE
University of Houston Clear Lake, Houston, TX June 2018-Present Research and Teaching Assistant
Technologies used: Python, Apache Spark, Hive, SQL, NetBeans
• Contributed to a research on authentication of gait patterns of people using Machine Learning Models.
• Provided academic mentoring on Data Science courses like Data Mining and Big Data.
• Taught students on courses such as Java, Data Structures, Algorithms and Cyber Security. Silection Art, India July 2016 – July 2017
Data Analyst Intern
Technologies used: SQL, Python, SSAS, SSRS, SSIS, Power BI, Azure, Microsoft Excel
• Created and managed database for an E-commerce website and executed SQL queries in Azure.
• Created ETL process from different sources and managed batch processing.
• Performed SQL query processing and Excel for cleaning and interpreting data from various sources.
• Prepared and cleaned data records and produced visualizations using Power BI.
• Extracted and identified metrics from raw data for analysis and reporting services.
• Responsible for analyzing sales and marketing data to improve internal functionality and support services. ACADEMIC PROJECTS
Credit Card Fraud Detection June 2018
Python, Scikit-Learn, Pandas, NumPy, Matplotlib, Seaborn
• Built Machine Learning model to predict results on an imbalanced credit card dataset.
• Applied algorithms like XGBoost, Random forests and Light GBM to find the probability of the data and generate ROC curves.
• Performed Exploratory Data Analysis and parameter optimization to improve performance of model.
• Achieved an AUC value of 99%.
Big Data Analysis for Netflix Recommendation data July 2018 Python, Spark MLlib, Hive, AWS EMR, MapReduce
• Implemented MapReduce algorithm to sort, split and reduce the data for accurate results.
• Executed Hive queries using EMR tool of Amazon Web Services (AWS).
• Developed a machine learning model using KNN algorithm for creating clusters of the data. Dimension Modelling for Dillard’s dataset March- April 2018 SQL, SSAS, SSRS, SSIS, Tableau
• Developed an effective multidimensional cube with OLAP operations and applying queries related to sales and marketing using Microsoft SQL Server Analytical Services (SSAS).
• Designed schemas and created reports for sales and marketing for the data.
• Built dashboards and created visualizations using Tableau and IBM Watson Analytics for analyzing sales and profits.