Srujana Nuthalapati

+1-313-***-**** adk0uz@r.postjobfree.com www.linkedin.com/in/srujanaraon/ Dallas, TX Education

Master of Science (GPA: 3.8/4.0) The University of Alabama in Huntsville Aug 2018 – May 2020 Major: Business Analytics

Bachelor of Technology (GPA:3.6/4.0) Jawaharlal Nehru Technological University Aug 2014 – Apr 2018 Major: Electronics & Communications Engineering

Skillset and Related Coursework

Programming Languages: Python (well versed with NumPy, SciPy, Pandas, Matplotlib, SciKit learn), SQL, C, R, Spark Frameworks & Tools: Tableau, PowerBI, Oracle Database, MySQL Database, AWS (Athena, Kinesis, QuickSight), IBM Cognos, Advanced Excel, Jupyter Notebook, PyCharm, RStudio, MATLAB, SAP Coursework: Data Analytics, Business Intelligence, Statistics, Machine learning, Anomaly detection, Big Data, Operations Management, Enterprise Resource Planning, Cyber Security Experience

Data & Finance Analyst, Nan McKay & Associates – Bridgeport Housing Authority, Bridgeport, CT Jan 2021 – Present

· Analyzed and visualized financial data in Power BI to identify significant differences, relationships, and trends in Program Integrity and Quality Control of the organization. Published live Dashboards in server to monitor KPIs of Customer Operations and Customer Care (servicing) productivity

· Analyzed past results, performed variance analysis of financial data, identified trends, detected outliers, and made recommendations for improvement.

· Pulled tenant data from Yardi and developed regression models to predict potential future participants and their income levels from wait list for housing choice voucher program.

· Created, analyzed, reviewed, validated and audited monthly reports to ensure accuracy and completeness of payouts.

· Supported management team in developing metrics and strategies for improvement of accuracy in financial reporting. Fulfilled ad-hoc requests, maintained, evaluated, and reported on recurring analytic studies. Data Analyst (Healthcare), Henry Ford Health System, Detroit, MI (Remote) Jun 2020 – Jan 2021

· In Python analyzed Health Care data by applying data extraction/data wrangling/data visualization/statistical assessment & machine learning techniques to derive actionable insights to optimize costs, improve products and services and implement care management programs for better health outcomes to HFHS members.

· Built ML model on diabetic patients to classify unmanaged population based on medical diagnosis codes, lab reports, vitals, pharmacy usage, demographic information & lifestyle attributes to improve patient’s health, enhance coordination of care.

· Investigated and created a visual story dashboard using Tableau for Non-Contractor provider charges across the United States to partner with providers and enhance the member experience.

· Created and maintained various data tables for project access. Cleaned, validated, and manipulated complex clinical datasets in order to create the data foundation for further analytics and the development of key insights (Oracle SQL, R, Tableau, Excel) Data Analyst, US Army CCDC Aviation and Missile Center, Huntsville, AL Jan 2020 – Apr 2020

· Identified key features and developed an R package that will easily allow SRP reliability engineers to generate graphs of missile component testing data and identify reliability trends with regards to age.

· Documented a user guide that includes clear instructions on tool use, explanations of tool functions, and possible future updates.

· Provided visualization of survey data using Tableau, drawing insights by segmenting data and using inferential statistics. Graduate Assistant, The University of Alabama in Huntsville, Huntsville, AL Aug 2019 – May 2020

· Troubleshooted errors, trained students in solving SAP (PP, MM modules) lab exercises and SQL querying in Oracle DB.

· Researched ‘Trends of product deletion rationalization methodologies’ by collecting information from over 20,000 research papers in the fields of supply chain management, marketing & strategy, engineering & design using text analytics. Data Science Intern, FORKaiA, Irvine, CA (remote) Feb 2019 – Aug 2019

· Consolidated data from different sources, performed exploratory data analysis, cleaned, and prepared the dataset for analysis.

· Predicted the likelihood of credit card defaults and identified the key drivers that determine the likelihood using logistic regression and CART with a hit ratio of about 83% each.

· Designed interactive dashboards on AWS QuickSight replacing the spreadsheets that were used to plan and allocate resources across agile teams in each value stream of the business, valuing over $6 million.

· Worked cross-functionally with teams to gather requirements and automate business reports by creating Tableau dashboards. Business Systems Analyst Intern, PZI International Consulting Inc., Huntsville, AL May 2019 – Jul 2019

· Determined the operational objectives of clients by studying business functions, evaluated output requirements and formats.

· Collaborated with stakeholders, business partners and management to collect, identify and prioritize business requirements.

· Studied and documented business processes by analyzing requirements, constructed workflow charts and diagrams. Data Analyst Intern, IComm Tele LTD., India Aug 2016 – Jul 2018

· Created interactive analytics reports by authoring SQL queries in IBM Cognos to provide insights on KPIs, task compliance and revenue trends to retail managers. Developed dashboard in Tableau to explain production statistics and preferences.

· Developed a configurable A/B testing product to evaluate the performance of different types of antennas and cables.

· Reduced inventory costs by 15% by predicting monthly sales of cable wires using time series ARIMA, linear regression.

· Analyzed cycle time data of machinery in SQL and recommended solutions to reduce machine downtime by 23%.

· Created, managed BOM, SOP, Product Routings & Groups for Fulfillment, Procurement, Production operations using SAP. Projects

New York Subway riders: Used Linear Regression to find out the effect of weather and other factors on ridership to the subway. Image Classification using PySpark: Classified 6899 images using Random Forests, Logistic Regression and Gradient Boosting. Runtime had been reduced by 33.3 minutes compared to HDFS and achieved 73% accuracy using Random Forests. Movie review recommendation using collaborative filtering in python: Designed algorithms based on gender and movie genre to predict movie ratings for 10M users. Predicted the movie ratings of targets using KNN for 50 similar users with 80% accuracy. Are Wealthier People Healthier? Extracted data from several online API’s, preprocessed, aggregated, and merged them in Python to perform analysis. Built dashboards using Plotly in Python to obtain interesting results of the correlation between health and wealth.

Credit Risk Assessment of Loan Applicants Employed and compared techniques like K-nearest neighbors, support vector machines and random forests in Python. Implemented Under Sampling for the data set reducing loss to the Bank from $1.1 Million to $650,000.

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