Social Media Data

JAYASHREE SUBRAMANIAN

Ph: 217-***-**** **** South Main Street #207 Murray, UT 84107 Email: ********@***.*** SUMMARY Masters in Computer Science with 3 years of professional experience in Data Science and Software Engineering, seeking a full time position from July 2020

EDUCATION

Arizona State University, Tempe, AZ Aug 2018 – May 2020 Masters in Computer Science GPA: 3.89/4.00

Anna University, Chennai, India Aug 2012 – May 2016 Bachelors in Computer Science and Engineering GPA: 8.98/10 State Rank: 18/20,769 TECHNICAL SKILLS

• Programming Language: Python, SQL, R, C, Java, SAS

• Databases and Statistical Software: Oracle, Teradata SQL, Scikit-Learn, NumPy, pandas, Tensorflow, Hive, PostgreSQL, AWS

• Data Analytics Tools and Technologies: Power BI, Tableau, Adobe Site Catalyst, Google Analytics, A/B Testing, JavaScript, D3

• Coursework: Statistical Machine Learning, Data Structures & Algorithms, Data Mining & Visualization, NLP, HCI, SEO, SEM PROFESSIONAL EXPERIENCE

Data Analytics Intern – DHL Express, Tempe, AZ, United States May 2019 – Aug 2019 Data and Text Analytics [Python, Microsoft SQL, Microsoft Access, Excel, PowerBI, UI Path, Clustering, Regression]

• Designed and published a weekly report to extract productivity of DHL, performed root cause analysis for customer calls

• Designed a visualization strategy to capture the trends of customer calls by integrating Traces, Complaints, and Claims data

• Automated weekly reporting using UI Path and developed bots through Robotic Process Automation (RPA) to automatically close First Time Resolution (FTR) and Quick Action Requests (QAR)

• Developed a Time series Forecasting Model to predict the issues; reduced the number of calls and queries by 5%

• Analyzed customer’s E-mail, Chat, Social Media data for pattern and prioritized critical issue resolution using Python

• Provided customer segmentation insights for B2B and B2C Calls using the Name Entity Recognition in Python Student Employee – Arizona State University, Tempe, AZ, United States Oct 2018 – May 2019

• Leveraged technology for a social cause by creating customized audible books (Text-Speech) for the students with print- related disabilities at Arizona State University

Analyst – Latentview Analytics Private Ltd., Chennai, India May 2016 – Dec 2017 Social Media [Python, R, Java, Impala SQL Server, Radian6, Microsoft Excel, PowerBI]

• Designed marketing campaigns based on social content shared (Twitter, Facebook, YouTube and News/Blog), refined the data sources and increased the traffic by 4%

• Performed Competitive Ad Analysis on large data sets to increase the social media presence and product purchase intent

• Facilitated instant decision-making using topic modeling and content analysis on conferences and events Digital and Paid Media [Propensity Modeling, Teradata SQL, Adobe Site Catalyst, Google Analytics, Excel, Tableau]

• Performed A/B Testing to understand the impact of all the experiments run over markets for different sets of audience

• Managed end-to-end web analytics support involving R&D, Business Case, Design, and Tracking for the marketing initiatives involving High-volume transactions on websites across Merchants and Consumers which increased the performance by 5-8% CRM Analytics [Teradata SQL, SAS, Statistical Analysis, VBA Macro, Tableau, Excel, Churn Analysis]

• Analyzed portfolio to understand the trends across merchant products which led to an increase in the adoption factor by 2-3%

• Extracted, Analyzed, and Illustrated the different data patterns to create consistent methodology frameworks ACADEMIC PROJECTS

Denoising and Stacked Autoencoders Oct 2018 – Nov 2018

• Built a denoising autoencoders from scratch in Python to reconstruct the images by adding Gaussian noise with minimal loss

• Developed a feature extractor using unsupervised learning and outperformed the baseline models with an accuracy of 72.8% PUBLICATIONS

“Exploiting Emojis for Sarcasm Detection”. International Conference on Social Computing, Behavior-Culture Modeling, and Prediction (SBP-BRiMS 2019), July 9 - 12, 2019. Washington DC pdf Nov 2018 – Feb 2019

• Proposed a novel framework to capture text and emoji signals, to learn complex sentiments for sarcasm detection

• Implemented LSTM with an attention layer and demonstrated the effectiveness of the framework with an F1 score of 0.987 on real-world Twitter and Facebook data

Contact this candidate