Data Python

Srikanth Reddy Cherukupelli

860-***-**** *************@*****.*** www.linkedin.com/in/srikanth-reddy-cherukupelli EDUCATION

University of Connecticut School of Business, Hartford, CT Dec 2019 Master of Science, Business Analytics and Project Management (GPA: 3.7/4.0) Osmania University College of Engineering, Hyderabad, India May 2015 Bachelor of Engineering, Electronics and Communication (GPA: 8.3/10) TECHNICAL SKILLS

Programming Languages & Tools: SQL, SAS (Base, Enterprise Guide, JMP, Miner), Python, R, Tableau, MS Power BI, Advanced Excel

(Functions, Pivots, Macros, Lookups, VBA, Solver), MS Power Point Databases: Oracle SQL, Microsoft SQL Server, MySQL, Teradata Techniques: Exploratory Data Analysis, Data Blending, Data Mining, Data Visualization and Reporting, Business Intelligence, Data management, Business Decision Modeling, Business Process Modeling, Statistical Analysis, A/B Testing, Marketing Analytics Healthcare Analytics, Data Modelling, Machine Learning, Regression, Classification, Web Analytics, Project Risk Management PROFESSIONAL EXPERIENCE

Stanley Black & Decker Inc. (Capstone Project) Analytics Consultant Aug 2019 - Dec 2019

• Developed interactive Tableau dashboard to visualize Freight spend of $300M for 350 carriers for years 2018-19

• Analyzed data in Python to identify potential cost reduction opportunities by truck load rounding (LTL to FTL); ensuring truck space optimization; cost saving up to $132K by switching carriers

• Used SQL queries, data warehousing techniques to leverage insights from multiple data sources

• Designed a recommender system to provide the best carrier option for any shipping condition resulting in cost savings by 13% Cleco Corporate Holdings LLC Data Science Intern May 2019 - Aug 2019

• Automated process of detecting critical outage patterns in data using Python; improving detection by 40%

• Reduced callouts by 20% and significant General & Administrative expenses by identifying location and frequency of real-time outages with Tableau dashboards in cross functional team environment

• Identified potential customers for Energy efficiency program by analyzing data from multiple sources in SAS using customers demographics, power consumption parameters

• Explored call center data in Microsoft Power BI; capturing major reasons for calls for better resource allocation Deloitte Touche Tohmatsu Limited Associate Solution Advisor Jul 2015 - Jul 2018

• Performed Exploratory Data Analysis in SAS, SQL and Excel to identify trends, anomalies. Develop ETL procedures and data pipelines in support of financial reporting for Fortune 500 companies

• Performed Data cleaning, Data mining leveraging information from Metadata and moved consolidated data to agile framework, automating the process after validating the business requirements

• Implemented hierarchical clustering to segment project contracts for revenue recognition through POC method; enhanced risk assessment methodology using Tableau dashboards

• Automated the process of extracting data samples using Business Intelligence tools; reduced turnaround time for ad-hoc requests from 5 days to 6 hours

• Consumer Analytics: Performed customer segmentation using RFM model, K-Means clustering. Suggested different ways to reach out to customers in different clusters and increased conversion rate by 21%

• Performed reconciliation for data quality and data profiling using SQL queries from multiple sources with various formats

• Supervised team of 4 analysts & interns for GL-TB reconciliations and samples extraction using SAS, ACL and Excel reporting

• Managed 20+ entities, interacted with audit teams on scoping discussions and ensured on-time delivery of project assignments Deloitte Touche Tohmatsu Limited Analyst Intern Dec 2014 - Feb 2015

• Developed scripts in SAS/SQL to read data extracts of various formats; standardized data manipulation for internal tools ACADEMIC PROJECTS & COMPETITIONS

• Voya Financial Data Challenge (Marketing Analytics): Python, SAS, Excel, Tableau Implemented Text Mining and NLP techniques to build a bag of words model; identified key words for Email subject lines, sweet spots for email volume and provided business recommendations to improve Click-through rate by 20%

• Insurance Fraud Analytics: Python, SAS, Tableau Performed data analytics on insurance claims data, identified key factors of Fraudulence, built classification models with accuracy of 76%

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