Data Engineering

RANJAN KUMAR

Houston, TX ***** 832-***-**** ****************@*****.*** LinkedIn GitHub

TECHNICAL SKILLS

• Programming: Python, Java, R, SQL Visualization: Power BI, Tableau, Matplotlib, Seaborn, ggplot2

• Tools: Selenium, UFT, TestNG, Eclipse, Jupyter Notebook, IBM Watson, HP ALM, Hadoop, Spark, Advanced MS Excel

• ML Packages: Pandas, NumPy, SciPy, Sci-kit learn

• Machine Learning: Linear Regression, KNN, SVM, Logistic Regression, Decision Tree, Neural Network

• Certifications: IBM Data Science Professional Certificate, Supply Chain Management PROFESSIONAL EXPERIENCE

Graduate Assistant, University of Houston – Houston, TX Jan2020- Dec2020

• Assisted instructor in preparation of course materials and exams, grading assignments, and proctoring exams.

• Assisted in the preparation and posting of grades Test Engineer, Infosys Ltd – Pune, India March 2017- June 2019 Client- Northern Trust, USA

• Experience working in software development life cycle (SDLC) from project initiation phase to post-deployment phase.

• Proficient in Project Management Methodologies like Agile and Waterfall model.

• Built complex SQL queries to verify data from Source to Target and performed data validation testing using SQL queries.

• Performing backend testing of the DB by writing SQL queries to test integrity of the application and Oracle database

• Developed a tool to automate HP ALM task using VBA and Macros. ACADEMIC PROJECTS

Housing Price Prediction [Python]

• Predicted housing sale prices in King County, USA using various machine learning techniques such as Linear Regression, Ridge and Lasso Regression, etc. on a dataset between May 2014 to May 2015

• Analyzed the data using Outliers Analysis, Linear Regression Model and test-train split to find a model that fit dataset well on Root Mean Squared Error (RMSE).

Loan Case Prediction [Python]

• Loaded a historical dataset from loan applications, clean data, and apply different classification algorithm on the data

• Built a Classifier to predict whether a loan case will be paid off or not using machine learning algorithm such as KNN, Decision Tree, SVM, Logistic Regression

• Results are reported as the accuracy of each classifier, using metrices such as Jaccard Index, F1-score.and Log Loss Fire Department Data Analysis [Power BI]

• Analyzed the San Francisco Fire department data of past 20 years to determine top 10 Station area associated with Incident Locations, most used unit types, top 5 call types received and zip codes with most calls received to provide quick response

• Determined the Average available time and Average on-scene time to decrease response time of Fire service department EDUCATION

University of Houston – Houston, TX

Pursuing Master of Science, Industrial Engineering Minor in Statistics (Data Science) GPA:4.0 Expected Dec 2021 Relevant Coursework: Probability Stat for Engineers, Operation Research, Data Analytics for Engr. Mgt, Cloud Data Visualization, Project Management, Statistical Methods in Research, Statistical Process Control Jaypee University of Engineering & Technology MP, India Bachelor of Engineering in Mechanical Engineering GPA:3.5 June 2016

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