Srujana Guduru

adex6c@r.postjobfree.com 513-***-**** www.linkedin.com/in/srujana-guduru

https://github.com/Srujanaguduru https://public.tableau.com/profile/srujana.guduru EDUCATION

University of Cincinnati, Carl H. Lindner College of Business, Cincinnati, Ohio August 2020 Master of Science, Business Analytics GPA: 3.9/4.0

• Relevant Coursework: Statistical Methods & Modeling, Optimization, Probability Models, Simulation Modelling, Applied Linear Regression, Data Mining, Python, Big data Processing, Data Management & Data Visualization Sreenidhi Institute of Science and Technology Hyderabad, India May 2016 Bachelor of Technology, Electronics and Communication Engineering GPA: 89/100 SKILLS & CERTIFICATIONS

• Programming Languages: Python, R, MS SQL, MySQL, SAS, Hadoop, Sqoop, Hive, Spark, PySpark, Cloudera, Databricks, AWS, Azure, MS Excel, MS Access

• Tools: Tableau, Power BI, Alteryx, Microsoft Office, Google Analytics

• Analytical Techniques: Linear Regression, Logistic Regression, Tree based models, KNN, K-Means clustering, Support Vector Machines, Cross Validation, Bagging, Boosting, Shrinkage Methods, Hypothesis testing, A/B testing, ANOVA, MapReduce, YARN WORK EXPERIENCE

L&T Metro Rail Hyderabad Limited (LTMRHL), Hyderabad, India July 2017 - July 2019 Senior Engineer

• Commuter analytics to determine the travel behavior patterns using Python and Tableau, provided the insights on payment, footfall, peak hours to the Operations and Marketing team which led to the increase of footfall by 5%.

• Performed customer segmentation using K-Means clustering in Python to direct marketing strategies to increase the card sales and commuter footfall.

• Achieved cost reduction of USD 8 Million by quantitative analysis on the material delivery data, installation data, testing data during Project acceleration and extension using Microsoft Excel.

• Analyzed the feasibility, pricing strategy and profitability from advertising and leasing in stations, malls, digital displays and provided insights to maximize the income.

• Prepared budget forecast, cash flow analysis and generated ad-hoc reports using SQL for management review and decision making.

• Extracted data using MS SQL and developed cashflow and payment dashboards using Tableau to address business problems and requirements.

Engineer July 2016 - July 2017

• Forecasted the footfall at each station based on the seasonality and trend analysis using time series ARIMA modelling which was used to effectively plan the operational resources to meet the KPIs.

• Classified the assets for the corrective maintenance using logistic regression on past fault history data which helped to plan the asset maintenance. This reduced asset fault frequency and increased the availability by 10%.

• Collaborated with operations, marketing, business teams and other stake holders to develop data driven insights and models which increase the revenue from external sources.

• Worked with Project Director for scheduling, tracking and monitoring the Project progress. Reported project progress and critical issues through presentations, reports and Tableau dashboards across various channels. American Modern Insurance Group, Cincinnati, Ohio Jan 2020- Apr 2020 Graduate Student consultant (Team lead)

• Developed a web application using R Shiny package in R to provide the descriptive analytics on the performance of the manufactured homes insurance product in the new IT system.

• Determined the home insurance policies which are most likely to be fraudulent using Random forest classification in R.

• As a team lead, implemented the Agile Project Management and resolved issues throughout the Project’s lifecycle. PROJECTS

Prediction of customer Charge off in Lending club

Skills used: Python (Pandas, Scikit learn)

• Performed Exploratory data analysis on Lending club data and predicted the charge off rate of the customer based on their income, employment, FICO scores and other factors using Logistic regression. Profitability analysis on Airbnb

Skills used: R Markdown, Time Series forecasting, Tableau

• Identified the most profitable zip codes in New York for short term investments using Airbnb and Zillow data set.

• Forecasted the current property price using the ARIMA model and identified profitable zip codes using payback period and break- even analysis.

Netflix Movie Recommendation System

• Built a movie recommendation system on Netflix data using Collaborative filtering i.e., based on the ratings of other users. Applied baseline methods and matrix factorization methods from Python Scikit library with the best test RMSE at 1.13.

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