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Data Science Professional

Location:
Houston, TX
Posted:
April 25, 2019

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Resume:

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.



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