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Click here or scroll down to respond to this candidateCandidate's Name
Email: EMAIL AVAILABLE Mobile: (Street Address LinkedIn: https://LINKEDIN LINK AVAILABLE EDUCATIONMaster of Science in Business Analytics, University of Illinois Chicago, Chicago, IL Dec 2023 Relevant Coursework: : Statistics for Business, Data Mining in R, Advanced Database management, Data Visualization, Marketing, Machine Learning Statistics for Business, Big Data, Advanced Text Analytics (NLP) Bachelor of Technology in Computer Science, Acropolis institute of technology and research, Indore-India July 2022 SKILLS Programming Languages: Python, R, Data structure. Database & Framework & ETL: Microsoft SQL, Oracle DB, MySQL, AWS-S3, Lambda, Azure Synapse, Pyspark Technologies: Machine Learning, Data Analysis & Visualization Tools: R-Studio, QuickSight (AWS), Plotly-dash module, Jupyter-Notebook, R studio, Google-Colab,Power- BI WORK EXPERIENCEStudent Aide (Research Assistant) : University of Illinois Chicago Department of Chemical Engineering September 2022-Present Part of the Dr. Vikas Berrys (Head of the Department) research group for analyzing different courses in the Chemical Department using Python Language and its packages Pandas, Numpy, Seaborn, Matplotlib and Plotly. Performed Explanatory data analysis and Analyzed data for around 3k students the last 5 years to identify patterns and trends to improve retention and attrition. Successfully identified areas for improvement which led to an increase in Identifying Students pattern by 5% on retention and attrition. Python Developer (Intern), PYTHONMATE, INDORE(MP), INDIA July 2021 - October 2021 Worked on a Spam Detection Analysis project in a team of 5 individuals where we filtered keywords used in solicited and unsolicited emails bythe help of Python libraries like NumPy, pandas, sklearn, matplotlib, nlkt. Developed a model using feature extraction and determining the top 30-40 words having the most appearances in these emails. PROJECTS1. PREDICTING MANIPULATORS FROM DIFFERENT COMPANIES USING R Tech-Stack: R, EDA, Classification ML Algorithms- Logistic Regression, Decision Tree, handling imbalanced Dataset using SMOTE and Sampling Techniques Balanced the Dataset using SMOTE and Checked for any Outliers Applied logistic regression, decision tree and XGBoost techniques to identify the most accurate algorithm to predicted manipulators2. DATA VISUALIZATION USING TABLEAU Tech-stack: Tableau, excel, EDA Extracted, cleaned, preprocessed, and analyzed Bureau of transportation statistics (BTS) data operating Table Created meaningful visuals to gain insights about on-time performance and competitive analysis of airline 3. INSIGHTS DERIVED THROUGH MENTAL HEALTH DATA Tech-Stack: EDA, python, matplotlib, seaborn, plotly and hypothesis Explore the effects of Mental Health on the Tech Industry Employees and the relation between Health Expenditure of a country and Health Expectancy from the world happiness report over the years. Performed data cleaning to remove noisy data and to generate a mental health score based on the survey questions instead of classifying it as a Boolean value.LEADERSHIP AND ACTIVITIESRepublic Day Parade and Prime Ministers Rally, New Delhi,India December 2014 January 2015 NCC Cadet(Brass Band),Rank A represented NCC Directorate at Republic Day Marching Contingent at Rajpath and Prime Ministers rally at NCC Ground Training and placement cell AITR Indore, May 2018 - April 2021 Student Representative Planned & coordinated final placements for 2019-20 batch and internship drives for 2016-20 batch |
