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NABIHA SHAHID
Aspiration Statement
“I am inclined towards a career in Data Science and Business Intelligence. I plan on utilizing my existing skills and developing new skills in order to achieve expertise. Further, I am looking forward to pursuing a masters in tech management at a point where I have gained industry experience alongside.”
Core Skills
- Data Science • • • •
- Python, C++, AngularJS
- Power BI, Tableau
- Microsoft SQL
- HTML, CSS, JavaScript
- Customer Relationship Management (CRM)
- Software Project Management
- Cross-functional Coordination & Collaboration
Academic Awards / Achievements
- 100% Habib University Merit Scholarship
- The first female to be selected as the President of the major Computer Science society at Habib University - Brain.Hack()
Experience
Leadership / Meta-curricular
- Habib University’s Code.Play (3.0) - President
- Hour Of Code ACM - President
- Brain.Hack() - President
- ACM HU Chapter - Chairman
- Certified Data Scientist - DataCamp
- Analyzing Big Data with Microsoft R - DataCamp
- Analyzing and Visualizing Data with Microsoft Power BI - Udemy
Internship / Volunteer Work
- IS Business Analyst - Reckitt (May 2020 - Present)
- BluTech Consulting - BI Consultant
- Hysab Kytab - Data Analyst
- Jaffer Brothers Pvt. Limited - Data Science Intern
- Porter Pakistan, Nest I/O - Research and Development Head
- Teaching Assistant - Habib University
- Volunteer - The Citizens Foundation
Publications / Creative Projects
- Developed a 2D game ‘Multiplayer Modernized Poker Game’ using OOP concepts and SDL 2.0 Graphics Layer.
- Developed a web based online portal for freelancing services ‘TaskMonkey’ using ASP.net MVC and web development tools.
Final Year Project
Project Title
Personalized Recommendation System for UBL’s Online Banking
Description
Our FYP is based with UBL digital Lab, we aim to make their mobile application smarter in order to make their local customer experience better by proving customized transactions and suggestions. According to UBL, no local financial institution or banks cater to the needs of their customer through an app providing completely customized transaction category recommendation system. Generally, the local financial market is focused on expanding market share rather than the retention of their customers. The proposed transaction category recommendation system is aimed at, both, obtaining new customers and retaining current customers by making customer service personalized and better. Our group have achieved this by using data science and machine learning algorithms. (Group Project)
Project Pictures
