Gawtam S Bhat

adjnqt@r.postjobfree.com 352-***-**** https://www.linkedin.com/in/infinitebhat/ https://infinitebhat.github.io/8/ EDUCATION:

Master of Science (M.S.) in Systems Engineering, University of Florida, US (3.47/4) Graduate Certificate in Engineering Project Management, University of Florida, US Jan 2019-Dec 2020

Bachelor of Engineering in Mechanical Engineering, Visvesvaraya Tech University,IN (3.57/4) Jul 2013- Jul 2017 TECHNICAL SKILLS:

Programming Languages: Python, R, SQL, Stata Data Visualization: Tableau, Amazon QuickSight Software Tools: Minitab, MS Excel, SAP ERP/Tally, MS Project, Solid Works, Mold flow Analyzer, ARENA AWS Data Analytics Fundamentals. PROFESSIONAL EXPERIENCE:

Graduate Teaching Assistant Department of Industrial and Systems Engineering Aug 2019-Dec 2020

• Contribute to the development of appropriate teaching materials to ensure content and methods of delivery meet learning objectives of Lean Production Systems and Manufacturing Management. Introduced paperless submission Exam evaluation. Assessed with the instructor the validity of the exam and assignment questions to properly test material learned throughout the course, with continuous feedback.

Data Analytics Intern Forage Pty. Ltd. Aug 2020-Oct 2020

• It was part of KPMG Virtual Internship Program. Analyzed and identified segments of customers with similar demand behaviors, historical purchases on basis of Recency, Frequency and Monetary values using K-Means algorithm. Recommended top 1000 customers to drive up sales and revenue. Tools used: Python (pandas, NumPy, sklearn, seaborn), Excel. Graduate Research Fellow Department of Industrial and Systems Engineering May 2020-Aug 2020

• Analyzed multivariate/binary image data using statistical monitoring techniques and improved the existing method of detecting defects on gray scale images of semiconductor materials.

• Performed application of Statistical Learning techniques like decision tree fitting, regression, EWMA charts, hypothesis testing on Stochastic Textured Surface data and achieved 89% accuracy level in detecting defects. R (rpart, stats, caret, ggplot2). Sales and Marketing Engineer Hydrotek Engineers, India Feb 2018- Sep 2018

• Led a team and Served as subject matter expert in sales team to forecast sales through Excel. Generated reports using Excel

(VLOOKUP, pivot tables), SAP ERP to implement exponential smoothing forecast techniques to predict demand and production number and successfully increased customer retention number by approximately 10% thus decreased product waiting time by 3 days.

• Increased revenue more than 12% through effective CRM and marketing techniques with B2B, B2C business additions.

• Presented quarterly sales report with KPIs to senior management using Microsoft PowerPoint Presentations, Tableau visualization. Engineering Intern Tata Power, India Jun 2015- July 2015

• Collected and segregated energy loss data in last 10 years by using SQL into different types. Later Analyzed YoY variation in power generation, power loss and loss incurred to company using Advanced Excel tools. PROJECTS:

Retail Demand Forecasting Project

• Analyzed approaches related to data preparation, analysis and forecasting of time series, with aim to facilitate recommending sales

& marketing strategies based on trend/seasonality effects using data from Kaggle with diverse characteristics such as stationarity, seasonality, residuals and sales data variance. Implemented and compared results using ARIMA, Facebook’s Prophet and LSTM Neural network. Tools: Python (pandas, sklearn, fbprnphet, stats, math, TensorFlow, keras). Classification of Audio Recordings Using Convolutional Neural Network (CNN)

• We investigate the performance of machine learning and neural networks on classification of human emotions in audio data. We utilize an ensemble of 4 finetuned CNNs following the Densenet architecture which are pretrained on the ImageNet dataset. We demonstrate that audio recording samples falling into eight emotive categories may be classified with 85.5% accuracy. (PyTorch) Regression Analysis of Tech Pulse Index

• Analyzed time-series index data and its correlation with tech industry, unemployment rate and Housing prices using statistical analysis techniques like Linear Regression, Probit, Logistic Regression and Hypothesis testing for stationarity. Tools: Stata Project Management Capstone Project

• Prepared project layout, WBS, organizational chart, Gantt Chart, progress assessment KPIs and project dashboard. Compared calculated Earned Value, Planned Value and Actual cost of project. Completed Risk Assessment and Risk impact Calculations using Monte Carlo Simulation and Presented the complete project report. Tools: MS Project, MS Excel, MS PowerPoint. Vehicle Routing Optimization with Capacity and Time Window constraints

• Implemented optimization algorithms to model and solve supply chain vehicle routing problem and optimized total cost by 17% and reduced total number of trucks purchased to 16 from 25, thus saving significant investment. The results were then compared with solution obtained with MS Excel. Tools: Excel-Solver, Python (or-tools, pandas, NumPy, Matplotlib).