Business Data Analyst

Leena Sherif

San Francisco Bay Area, California

***************@*****.*** – https://www.linkedin.com/in/leenasherif/ – https://github.com/leenasherif - 408-***-****

Professional Profile

An astute Data Analyst with experience working in a fortune 500 company with over 258,700 employees. Capable of contributing to major data analytics projects; effectively utilizing computer programs, communicating across teams, and introducing new data methods. With a successful track record managing data processes, from analyzing existing datasets and identifying relevant data metrics to producing dashboard visualizations. Possessing excellent communication skills, effectively engaging diverse stakeholders. Recently completed a 16-week Data Science programme, developing a robust understanding of how to use new technologies and coding to understand, visualize and clean complex datasets and apply machine learning. Fascinated by the opportunity to use machine learning in addressing contemporary media/tech challenges.

EDUCATION

Masters of Arts in Applied Economics Concentration in Programming, San Jose State University GPA: 3.70 2017 - 2018

Study Abroad Masters in Data Science, R, Utretch University, The Netherlands GPA: 4.0 2018

Thesis research resulted in an authored paper by Leena M. Sherif titled “Do more children cause mothers income to decrease?”. Presented at the Leon Panetta Lecture Series in Monterey, California (2018)

Dean’s List & Honors Graduate

Bachelor of Science in Economics, San Jose State University 2012 - 2016

Dean’s List

CERTIFICATIONS

Data Science and Machine Learning Bootcamp; Python, R, and SQL, Xccelerate Institution, Hong Kong July 2019

Google Individual Qualification (IQ) June 2019

California Real Estate License May 2020

TECHNICAL SKILLS

Python

Tableau

R

MySQL

Critical Thinking

Google Analytics

Microsoft Azure

Data visulization

STATA

Machine Learning

Deep learning

Power BI

EXPERIENCE

San Jose Sharks – San Jose, CA November 2019 – Present

Business Intelligence Analyst

Executed and presented various revenue generating ideas such as Dynamic Pricing and fee pricing resulting in a 25% increase in ticket revenue.

Conceptualized, executed and created reports for Sharks customer research surveys.

Build customized reports, dashboards, and tools for multiple departments to utilize from an every-day perspective to executive-level reporting.

Collaborated cross-functionally with Marketing, Ticket Operations, and Sales Team to developed reports and dashboards utilizing SQL, Tableau, and Excel to measure the success of campaigns and Dynamic Pricing initiatives.

Queried segmented target groups from SQL to input into Tableau to analyze and generate a final dashboard for various stakeholders.

Planned roadmaps, documented data structures, and administered Data Warehouse in a SQL Server environment.

Utilized R to run several multiple linear regression analysis and ANOVA’s on the full spectrum of pricing.

Utilized SAP Marketing cloud sales platform and SAP Hybris to gather data and perform analytics.

Wells Fargo – San Francisco, CA August 2017 – February 2019

Data Analyst

Extract, manipulate, reconcile, and analyze large datasets through MySQL and excel.

Create Tableau dashboards to communicate key KPI findings and statistical results to various stakeholders.

Assist in developing the spreadsheets that would eventually create the final data for a completed audit.

Conducted polling interview calls to gather information from Retail Bank customers to assist with compiling research to confirm or deny case allegations.

Authored a process guide to help the Wells Fargo Risk/Quality Assurance Management team accurately report and maintain the integrity of data to support internal audit.

Scottrade – Pleasanton, CA January 2017 – August 2017

Investment Analyst

Develop and maintain relationships with prospective and existing clients.

Establish and maintain various client databases in order to ensure that information is easily accessible.

Identify client needs by developing investment strategies and establishing long-term goals.

Prepare investment materials and distribute to prospective clients.

PROJECTS

Xccelerate Capstone Feb 2019 – Jul 2019

Topic: SenseFashion – An Automatic Labeling System for Online Fashion Retailers

Preformed exploratory data analysis (EDA) for clothing types and developed an automatic labeling system for fashion online retailers deployed as a full-stack web application. Specific identified attributes can further be categorized as styles of clothing and user recommendations can be made.

Investigated several academic papers referring us to DeepFashion data and FashionNet model. Manually cleaned folders from DeepFashion and sorted according to one feature (print, fabric, clothing type).

Effectively utilized machine learning and deep learning technologies, such as VGG 16 (algorithm) a pertained model on Imagenet and built on top of it with transfer learning with the goal of changing the output layer to include: 11 patterns, 10 fabrics and 17 clothing types. In total, we used 800 images per class.

Employed data augmentation techniques such as rotation, brightness, zoom, size, learning rate, epoch’s in order to address overfitting/ under fitting. Overall, increased accuracy to a desirable >70%.

Python Capstone Project: Oct 2018- Dec 2018

Topic: Stock Price Analysis

Developed an algorithm in Python that requests the user to enter a stock symbol and a duration for which the analysis to be performed.

Utilized google finance API to acquire stock pricing available in the last 5 years for entered stock and store it in database.

Utilized “GAP Analysis” on daily charts to determine if there are any GAPS in the price throughout past 5 years.

Utilized R to create visualization API such as ggplots to chart the stock and show the unfilled gaps.

Econometrics Thesis Research Project: Oct 2017- Dec 2018

Topic: Do more children cause mothers income to decrease?

Utilized data software R, and python to deduce results from data gathered from the U.S Census.

Analyzed data from over 2 thousand households in the Silicon Valley across one time period.

Confirmed hypothesis that data supports a relationship between number of kids and decrease of wages through regression analysis.

AWARDS

California State Community Service Award

Santa Clara County Dept. of Education for Outstanding Academic Achievement Award

ADDITIONAL SKILLS

Fluent in Arabic.

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