Business Process Analyst

Mehul Sharma

*****.**.******@*****.*** 480-***-**** https://www.linkedin.com/in/mehul-bs-sharma

EDUCATION

Master of Science in Industrial Engineering August 2019 – May 2021

Arizona State University, Tempe, USA GPA – 3.4/4

(Courses – Statistical Learning for Data mining, Data Science Decision Analysis, Regression Analysis, Advanced Stochastic Operational Research, Advanced Deterministic Operational research, Production Systems, Advanced Quality Control

Bachelor of Engineering in Mechanical Engineering August 2015 – May 2019

Gujarat Technological University, Ahmedabad, India GPA - 8.0/10

TECHNICAL SKILLS

Programming Language: Python, R, SQL, Visual Basic, AMPL

Statistical Tools: SAS, JMP, Minitab, MS Excel

Visualization Tools: Tableau, QlikView, Python matplotlib

Database: MySQL, SQL Server, Oracle SQL Developer, Toad, PostgreSQL, MS Access

Tools: Visual Studio, Jupiter Notebook, Jupiter Lab, Agile, git

WORK EXPERIENCE

Business Process Analyst Intern – Cavalry Portfolio Services, Phoenix, USA April 2021 – Present

Enhanced capacity efficiency for placing more accounts by modeling priorities of multiple placements.

Updated the cost penalizing model for multiple placement account to increase the profit to the company.

Enhanced understanding experience of each individual account by fine-tuning stored procedures & SQL queries for efficient data retrieval from 2M records.

Build and maintain Statistical models to optimize and improve collection efforts.

Software and technical skills used – Oracle SQL developer, QlikView, Excel, and Python.

Teaching Assistant – Arizona State University, Tempe, USA May 2020 – May 2021

Managed over 180 Students by ensuring seamless delivery of course content to achieve an academic success of 100%

In-person meetings and teaching of topics like Data Preparation, Machine Learning, and Data Mining and Visualization

Teach Labs for software’s like JMP, Tableau and MS Excel for topics like K-means clustering and hierarchical clustering.

Supply Chain Analyst intern – Orient Cement Ltd, Telangana, India Dec 2017 – March 2018

Improved the overage cost, holding, and inventory holding capacity by eliminating the surplus inventory production.

Optimized python scripts and SQL queries to perform data cleaning and feature engineering based on business rules & workflows on Millions of records loaded from Big Query.

Forecasted the demand using the ARIMA model in python, with an accuracy of 94% and RMSE of 0.42.

Software and Technical Skills Used – Python, SQL, Excel, and Tableau.

INDUSTRY PROJECTS

Predicting of Monthly Electricity Consumption and Monthly Maximum Temperature Jan 2021 – April 2021

Analyzed the temperature time series data and built Holt -Winter forecasting Model and ARIMA Seasonal Model in Python software to forecast future seasonal temperature in city.

Developed transfer function model to illustrate the relationship between Electricity Consumption and Maximum Temperature and achieved forecasting accuracy of 97.6% using Seasonal ARIMA model in temperature forecasting.

Prediction using ML – Diabetes problem Aug 2020 – Dec 2020

Split the data into testing and training. Trained models using algorithms and classifiers like Support Vector Machine, Multi-layer perceptron (Neural Network), Random Forest and Ada Boosting Classifier.

The Model was tested by calculating the generalization accuracy rate and a balanced error rate along with confusion matrix from K-Fold cross validation and the best model performed was Random Forest with accuracy of 86.07% and BER of 0.266.

Generalized Lot Sizing – Production-Warehousing Model Aug 2019 – Dec 2019

Generated a Google Map API Key to access and retrieve data from Google maps by Python code to produce the distance matrix for 25 nearby most populated cities to the metropolitan area of Saint Petersburg in Russia.

Developed a Mathematical Mixed Integer programming model and using AMPL with CPLEX solver mode optimal decisions to locate multiple production units and warehouses within the set of constraints to meet the quarterly demands of each city.

Optimized cost from 143 million to 32 million including holding, transportation, production, and other fixed costs.

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