Jyotsana Yadav

Jersey City, NJ ***** ac51rh@r.postjobfree.com 551-***-**** https://www.linkedin.com/in/jyotsana-yadav EDUCATION

Pace University, Seidenberg School of Computer Science and Information Systems New York, NY Masters of Science (MS) in Information Systems Major: Database Management System GPA 3.97 May’18 Maharshi Dayanand University Rohtak, India

Bachelor of Technology (B Tech) in Electrical Engineering June’12 CERTIFICATIONS

• Master Course in Tableau 10 for Business Intelligence - Certificate No: UC-GEXE1PN8 UDEMY

• Data Visualization with Python - Certificate No: a3371b0777f44feb997b738f290c8330 IBM Cognitive class RELEVANT COURSEWORK

Database Programming Big Data Database design & web development Data Warehousing, Mining & Visualization Database Management Systems Data Analysis for Decision Making Machine learning TECHNICAL SKILLS

Languages : SQL, XML, R, Python, QPP

Softwares : MySQL, Oracle SQL developer, MS-Excel,SAS, GIT, Hive, Impala, Anaconda (Jupyter, Rstudio),SRSS, Tableau, Eclipse Cloud : IBM Bluemix, Google Cloud, Cloudera

Others : Hadoop, Apace Spark, Unix, Linux, Docker, JIRA, SharePoint, Bugzilla PROJECTS / Git-hub

Data Analysis on Box-Office Releases Statistical modelling, MS-Excel (StatTools-Palisade)

• Analyzed the patterns in Box-office Data 2009-2017 & used linear regression to predict worldwide gross for the upcoming movies.

• Prepared the dependencies, statistical chart analysis, hypothesis testing reports using StatTools – Palisade & recommended the ideal time for the release of a movie to maximize performance at the box-office Relational Database for Event Management Data modeling, MySQL, Microsoft Visio

• Created and implemented ER modeling (ERD) using Microsoft Visio to understand the relations of different tables.

• Designed relational database using stored procedures, functions, cursors to organize data in an efficient manner for the automation of event management in the University using MySQL Analysis of Churn Dataset Python, K-Means Clustering, pandas,

• Performed a cluster analysis on the customer service dataset from a telecommunication company and suggested the factors depending on the churning of customers.

Titanic machine learning from disaster Python, scikit-learn, numpy, matplotlib

• Used Logistic regression on Kaggle dataset “Titanic: Machine learning from disaster” to predict the survival of passengers with the accuracy of 80%

EXPERIENCE

TATA Consultancy Services– Business Data Analyst (Client-side) Johannesburg, South Africa Client: NedBank Dec’15 - Oct’16

• Managed projects by participating in client meetings & JSE driven workshops to identify & translate the business requirement into technical specifications, BRDs for the offshore development team.

• Extensively worked on SQL by writing complex queries to provide macros, ad hoc reports on daily, quarterly basis to clients

• Worked on large datasets using Oracle SQL developer updated tables, views, triggers as per the requirements.

• Participated in client analytics projects with complex ETL processes for data mining and validation by using Rapidminer

• Worked with client team to build business reports & dashboards by using tools like Tableau, MS Excel

• Served as a consultant for project management, timely delivery and progress to prepare a proper UAT/QA environment ensured application runs successfully without bugs by tracking/maintaining JIRA, Bugzilla within sprint deadline. TATA Consultancy Services –Software developer and Analyst (Financial services) Haryana, India Client: Standard Bank of South Africa, First National Bank March’13 - Nov‘15

• Customized the application TCS B@NCS by writing UI/Business validations to adhere to the rules and regulations of JSE.

• Designed and developed new interfaces for processing Bloomberg and DTCC feeds files using XML, XSLS

• Worked under agile methodology & developed core modules for security processing components using QPP, Shell Script

• Resolved moderate to complex system issues, with focus on elimination of recurring problems reported by clients through troubleshooting

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