Neha Gour

Dearborn, MI +1-313-***-**** ad2r7g@r.postjobfree.com http://linkedin.com/in/neha-gour-554664271

A highly motivated and dedicated student pursuing an M.S. in Business Analytics with a major concentration in Finance, seeking to leverage two years of experience as an application development analyst to obtain a challenging role in a reputed organization.

EDUCATION

University of Michigan, Dearborn – Dearborn, MI January 2023 - December 2024

Master of Science, Business Analytics (Finance)

Devi Ahilya University – Indore, IN July 2020 - March 2022

Master of Science, Mathematics - 3.73/4.0 GPA

Maharaja Ranjit Singh College of Professional Sciences – Indore, IN July 2017 - March 2020

Bachelor of Science, Mathematics - 4.0/4.0 GPA

WORK EXPERIENCE

University Of Michigan - Dearborn July 2023 - December 2023

iLabs e-Cities research Project Intern

Conducted comprehensive research on 273 Michigan communities, analyzing taxes, assets, and property values.

Utilized advanced data analysis to calculate growth rates, creating visualizations and reports for stakeholders.

Developed a performance ranking system and collaborated in a multidisciplinary team for the e-Cities project's success.

Demonstrated attention to detail, analytical skills, and data proficiency.

Provided actionable growth recommendations, gaining valuable hands-on experience and professional growth.

Precision Engineering Works – Itarsi, IN July 2020 - December 2022

Application Development Analyst

Collaborated with senior developers and project managers to design, develop, and maintain software applications.

Conducted software analysis, testing, and debugging while addressing issues identified in code reviews.

Managed multiple projects successfully, adhering to budgets and contributing to internal development standards.

Improved application performance through code optimization and efficient algorithm implementation.

Stayed current with industry trends and technologies through training and cross-functional teamwork, including QA testing.

SKILLS

Technical Skills: Project management, Data Visualization, Data mining, applied forecasting, Accounting and Finance, MS Office, Data Analysis, Quantitative research, and analysis.

Data Analysis: Python, SQL, Statistical software (e.g., SPSS, R), Power BI, SAS, Simio, Minitab, JMP, Tableau

Organizational Skills: Documentation, data management, time management, data Collection, and Organization

PROJECT EXPERIENCE

Flint Water Replacement Project August 2023 - December 2023

Business Analytics Consultant: Data Minning

• Collaborated with a multidisciplinary team to address the water crisis in Flint, Michigan, by leveraging predictive analysis to identify areas in need of water service line replacement.

• Applied advanced statistical modeling techniques using JMP Pro to analyze Flint parcel data, identifying high-risk areas for infrastructure investments.

• Developed a classification model to predict the likelihood of water service line replacement based on historical records and water test results, achieving an AUC of the ROC as the performance evaluation criterion.

• Utilized Tableau for data visualization to uncover patterns and insights in the dataset, enhancing the interpretability of the analysis results.

• Prepared and delivered a 15-minute pitch presentation to top management, effectively communicating project goals, methodology, and key findings.

• Contributed to creating a comprehensive project report, detailing the analysis, methodology, and recommendations for future action.

• Provided detailed instructions for running the analysis and scoring the test dataset, ensuring reproducibility and ease of implementation for stakeholders.

This project showcased my ability to apply data analytics and predictive modeling to address real-world challenges, highlighting my skills in project management, data analysis, and communication with stakeholders.

Texas Coal Consumption Forecasting Project August 2023 – December 2023

Data Science Analyst: Applied Forecasting

• Collaborated in a team of four to analyze Texas coal consumption data and forecast future consumption using applied forecasting techniques.

• Utilized time series analysis, Winter's method, and ARIMA models to identify patterns and trends in the data for accurate forecasting.

• Collected data from GitHub, an open-source platform, and conducted thorough analysis and interpretation of quarterly coal consumption figures from 2001-Q1 to 2020-Q4.

• Applied multiplicative decomposition to understand trends, seasonality, and autocorrelation in the data, leading to valuable insights into the factors influencing coal consumption in Texas.

• Implemented Winter's Method, adjusting for trend and seasonal variation, and ARIMA models to generate accurate forecasts for the next four quarters of 2021.

• Conducted thorough model evaluation, including Mean Absolute Percentage Error (MAPE), Mean Absolute Deviation (MAD), and Mean Squared Deviation (MSD) to assess forecasting accuracy.

• Presented findings and forecasts through clear and concise visuals, including residual plots and forecast comparisons.

• Provided comprehensive conclusions and recommendations based on the comparative analysis of Winter's method and ARIMA models for forecasting coal consumption.

• Demonstrated proficiency in time series forecasting, data analysis, and communication skills through effective collaboration with team members.

This project not only showcased my ability to apply advanced forecasting techniques but also demonstrated strong teamwork and communication skills in presenting complex analytical findings.

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