Information Technology Data

JAYSHREE GOKULDAS WAYKOLE

** *** ******, ********, *** Jersey - 07029 Cell: 862-***-**** ***************@*****.*** LinkedIn Account Link to Portfolio GitHub Account Recommendation Letter SUMMARY:

• 3 years of combined experience in Data Science, Web Development and Full Stack Development.

• Proficient knowledge in Data Analytics and use of BI tools to make effective business decisions from data analysis.

• Experience in building machine learning models using Python for recommendations and classification.

• Experience in developing and analyzing performance of Ecommerce websites and defining and evaluating KPIs for them. EDUCATION:

Master of Science in Management of Information Technology GPA: 3.81 Rutgers- The State University of New Jersey. Dec 2017 Bachelor of Technology in Electronics and Telecommunication GPA: 9.21

University of Pune.

May 2014

TECHNICAL SKILLS:

• Analytical: Python (NumPy, Pandas, Scikit learn, Matplotlib, Seaborn, Plotly, Cufflinks), R, Tableau, Google Analytics.

• Database & Cloud Services: SQL, MySQL, Amazon Redshift.

• Data mining: Regression, Classification, Association mining, Clustering, Outlier Detection, Hypothesis testing.

• Others: Advanced Excel, Java, HTML, CSS, JavaScript, jQuery, PHP, Bootstrap, Responsive design, GitHub.

• Certifications: Web Analytics, Python for Data Science and Machine Learning (Udemy). WORK EXPERIENCE:

Discovery Communications: Product Design Research Intern New York, May 2017-Aug 2017 Project 1: Look-Alike Model for content recommendation to customers: (Investigation Discovery Network)

• Design hybrid recommendation systems (Item based collaborative filtering model + Classification based model).

• Existing Customers: Extract data (500k records) from different vendors stored in Amazon Redshift using nested SQL queries, use Item Based Collaborative Filtering model and create a normalized co-occurrence matrix for various shows in Python and calculate the weighted sum to recommend the shows with the highest sum.

• New Customers: To address the cold start problem with new customers use classification model based recommendation. Use wrapper feature selection techniques to determine the best user attributes and develop a model using proximity calculation methods in Python to relate interests of customers and recommend shows accordingly. Project 2: Analysis of Hamburger menu VS Tab bars for UI of TLC:

• Identified that the menu bar on home page had the highest number of user interactions by examining heat maps using Crazy Egg tool and noticed that home page had high bounce rates using Google Analytics data.

• Designed a hypothesis to implement hamburger menu to improve user experience on home page and examined results using A/B testing and Feedback from actual users (User Testing tools) which led to the reduction in bounce rate on home page. Project 3: User Journey study for personalization of Websites (Discovery, Animal Planet, TLC):

• Used website data to study trends in customer behavior using SQL, Google Analytics, Excel and created report on the actual VS expected user journeys. Recommended personalization based on analysis for each channel that will lead to improvement in user engagement, increase in traffic to website and time on site as well as reduce the bounce rates from websites. Rutgers Business School: Graduate Assistant Newark, Oct 2016-Present

• Designed web based budgeting system to enhance accuracy in maintaining budgets of Rutgers University using JavaScript, jQuery, Bootstrap, HTML, CSS. Wrote nested SQL queries to bring/send data to/ from UI from/to database with 10k record. Cybage softwares Pvt. Ltd: Data Analyst Pune, June 2014 to June 2016

• Analyzed website data and heat maps using Python, Google Analytics, Excel to identify areas of improvement and designed hypothesis for improving website performance and meet business KPIs and examined result of hypothesis using A/B testing.

• Developed E-commerce responsive web interface using HTML, CSS, JavaScript, jQuery and Bootstrap for some websites which led to increase in user engagement with the website by 6%. ACADEMIC PROJECTS/ COURSES:

Barkly Services customer base improvement (Market Research and Analytics):

• Performed regression and hypothesis testing in R programming and Tableau. Determined major factors that interested customers in selecting dog walking service and helped Barkley to design strategy to increase customer base by 12%. Student Alcohol Consumption Pattern Analysis:

• Preprocessed the dataset from Kaggle.com and applied classification algorithms using Python (Numpy, Pandas, Scikit learn) to determine top three factors leading to increase in alcohol consumption in students and helped Universities to efficiently design measures for decreasing Alcohol consumption. Created a visualization tool in Tableau for the analysis. LEADERSHIP EXPERIENCE AND PUBLICATIONS:

• Led a team of four and proposed a new algorithm to detect and track humans in MATLAB to enhance security on National borders and published a paper on ‘Human Detection, Tracking and Its Applications in Defense’.

• Mentor and assist Graduate Students in course selection at Rutgers University.

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