B.Tech (Computer Science Engineering)
Amity University, Noida
CGPA is 7.06
Process oriented data analyst with almost 3+ years of experience. Experienced in interpreting and analyzing data to drive growth, Furnish insights, analytics, and business intelligence needed to guide decisions. Passionate about studying how to improve performance. Seeking to leverage data analytical skills to improve corporate performance as a data analyst. Strong experience in quick turnaround of PoC’s by leveraging analytics, Data analysis , Visualization , Statistical algorithms like Forecasting, Decision-Trees, Logistic Regression etc.
CGPA is 7.06
Passed The Beginner's Module with 92%
Successfully completed and certified.
Passed with 80.2% (Grade: A2).
Passed with 9.4 CGPA.
Client: HKAA (Hong Kong Airport Authority)
Working for a pharmaceutical client, and developing their user specific dashboards and visual reports using Tableau Desktop 10.2.
1. Understanding the requirements of the client.
2. Developing Tableau visualizations and dashboards.
3. Restricted data for particular users using Row-Level security and User Filters.
4. Created action filters, parameters and calculated sets.
5. Developed workbooks to show Year over Year, Quarter over Quarter, YTD, QTD and MTD type of analysis.
6. Responsible for interaction with business stake holders, gathering requirements and managing the delivery.
7. Developed multiple charts like Area, Line, Needle, Gant, Pie, Donut, Bubble Charts, Maps etc.
Client: MORGAN STANLEY
Working for Morgan Stanley in their Enterprise Infrastructure, Technology, Data and Security supported applications, End User Computing, User Productivity Applications and Collaboration Tools.
1. Part of EIQA-QAPM (Enterprise Infrastructure & Quality Assurance - Quality Assurance & Product Management) team, doing Manual Testing.
2. Working on HP-ALM, Galaxy QA, Sharepoint.
3. Working on Multiple testing requests for UI and it's applications, and updating status on SharePoint.
4. Track records for multiple things on MS Excel and reporting them to managers.
5. Handling more than 40+ Applications on Morgan Stanley Enterprise Desktop Environment.
6. Sending Daily Status Report, Daily Observations and QC raised defects to manager.
7. Knows the workflow of all the basic applications of Morgan Stanley. (3D, Galaxy QA, Loans IQ, JellyBean etc.)
Client: BANK MEGA
Worked for two major clients with enormous data (in millions), and getting involved in end to end process from Data Loading -> Data Enrichment -> Initial Data Analysis -> Data Profiling for Churn -> Advance Data Analysis.
1. Identifying structure of data, format of various attributes, performing data validation while Data Loading through OpenText qLoader.
2. Uploading this data to Text Analytics software and getting sentiments of each log using Sentiment Analysis Engine.
3. Preparing data and enriching it by dividing it into filters and segment wise.
4. Doing Initial Data Analysis using Cross Tabs and Venn Diagrams, or simple line graphs.
5. Doing Advanced Analytics to predict future events, to give better insights of trends and patterns.
6. Use Machine Learning Algorithms of Analytics Tool like Forecasting, Decision-Trees, Logistic Regression etc.
Completed Live Project Training in Android
Successful completion of R online course and passed with 91%
Successful completion of Semester-6 at Amity, Dubai with Grade 8.31
Successful completion of 4-credit course of Android Development
Successful completion of Core Java
Successful completion of Certification in Web Component Development using Java EE as a part of OWDP
Passed with A+ grade
Passed with A+ grade
We have analysed their 2.4 Million + credit card customer data and given them insights about their active customers from past 3 years, % of actual churn, customers without savings account and just credit cards, defaulters, customers who might default in future. We did customer profiling on the basis of sentiment score got through Sentiment Analysis Engine. We made filters on transactions by year, transactions by month, transactions by week, age band, salary, CLV Band, frequency of transactions, region and sentiment score.
I have analysed 5 Million + data involving various databases of weather, flights, shopping, gates etc. We gave them useful and important business insights stating the right location of shops on the airport, to maximize the sales, and putting them active during specific time periods, also giving them insights about number of customers from each gate at particular time period. Made various reports and dashboards using Tableau Desktop 10.2.
I have analysed enormous amount of data (in millions), and performed the entire process from end to end from collection of data from various sources to loading data and performing some rules for data quality and put data fit with the business rules and then finally developed management-level specific dashboards.
It is a JAVA application that has been built using Visual Studio and SQL Server. In this project, i have used a real-time-data set of more than 6 Lac entries from which i have used 20% to for training and the rest for testing. I have applied two algorithms: Association Rule Mining and CURE Algorithm in order to get the results. The software generates graphical representation of the no. of complaints in each year from 2011-15. The project concludes that Cure Algorithm is more efficient, fast and reliable than Association Rule Mining.
I learnt the trade life cycle, worked with professionals of capital markets domain, had hands-on of how stocks order are placed through an exchange, did stock analysis, made reports, learnt financial terms and working.