Python Assistant

SANJANA SURESH

*******.******@****.***.*** https://www.linkedin.com/in/sanjanasuresh2493/

https://github.com/Sanjana2493 Phone No: +1-682-***-**** PROFESSIONAL SUMMARY

● Diligent and result-oriented Business Process professional with 4 years of experience in translating user requirements into application features using .NET, Python and SQL.

● Developed functional tools in Python to increase operational efficiency, automate and optimize processes.

● Experienced in text analytics – cleaning textual data, recognizing patterns in text through clustering using Kmeans in Python and classifying text using deep learning modules in Keras and TensorFlow. TECHNICAL SKILLS

Technology/Programming Languages:C, C#, Python (NumPy, Pandas, Matplotlib, Nltk, Pillow, Sklearn) R, BizTalk Technology Database Management:MySQL, Oracle SQL

Microsoft office:Excel (Vlookup, Pivot Table, Power Pivot), Word, PowerPoint Other Tools:Data mining using Weka, Tableau

PROFESSIONAL EXPERIENCE

Tata Consultancy Services: Walgreens Boots Alliance Client (Data Services Analyst) November 2011 - Present Focused on improving operational and maintenance processes through data science techniques and model building on operational data utilizing Python and Microsoft Excel.

● Presented 150 plus automatable use cases, with the acceptance rate of 75% by analyzing operational data - reduced maintenance time and efforts

● Built a model for Incident root cause analysis with an accuracy of 86% by analyzing the Incident description and resolution entered by users, through text analytics using NLTK, text clustering using Kmeans and text classification using Keras sequential model in Python

● Built a forecasting model to predict incidents per day in future with r-squared of 62% by analyzing historical incident data using neural networks in Python

IQuest Solutions Corp: Capital One Client (Software Engineer) August 2019 - November 2019 Focused on creating tables in Snowflake by extracting data from Amazon S3 according to business requirements.

● Created two relational databases in Snowflake as per the requirements provided by the data modeler

● Extracted data from Transactional database, aggregated numeric data to create metrics and stored the KPI information in a separate table

The University Of Texas At Arlington: Department of Management (Graduate Teaching Assistant) June 2018 - May 2019 Focused on collecting 10k filings and annual reports of organizations from FY08 to FY19, automating reporting processes, and reducing repetitive, manual tasks by utilizing Python.

● Enabled automatic generation of an Excel report of number instances of required keywords by developing a tool that read the financial reports of various organizations using Python, thereby optimizing work and increasing operational efficiency by 48%

● Read annual reports of 350 plus organizations (FY08 – FY18) and produced a report with the number of instances of data science-related terms using the developed tool

Accenture: UK based insurance client (Application Development Analyst) August 2015 - July 2017 Concentrated on collecting business requirements and modifying existing .NET and XSLT code for two specific sprints, as well as engaging in the documentation of five sprints at each stage of its SDLC.

● Monitored the status of 1000+ XML messages per day transferred electronically by BizTalk, stored in a SQL database

● Queried the status and other features of messages from SQL database for root-cause analysis in case of discrepancy

● Provided money savings and enabled business process continuity by fixing application bugs through resolving 10,000+ incidents classified as a high/medium/low priority according to the SLA standards

● Resolved all incidents achieving Live Service (LS) score of 100%. Served as a Subject Matter Expert of LS and received magic box award for the same

EDUCATION

M.S in Information Systems, The University of Texas at Arlington May 2019 (GPA 3.9/4) B.E in Electronics and communications,Visvesvaraya Technological University June 2015 (GPA: 3.3/4.0) PROJECTS

Sales Analysis of Pier 1 Imports’ Products: Analyzed real-time data of Pier 1 imports and gained insights about the highest selling products, seasonal sales, and online and offline purchases using Tableau. Performed sentiment analysis on 1000 plus customer reviews to analyze purchase patterns and preferences. Classified products as successful and unsuccessful with 78% accuracy using machine learning. Presented in front of a technical audience at the 4th Annual Analytics Symposium and secured runners up position.

Image Recognition - Cifar 10 Data set: Extracted the pixel values of 60,000 images each of size 28*28 pixels using the Python pillow module. Implemented Random forest Spark ML to classify the images based on their pixel values with 58% accuracy.

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