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Kushagra Sen
  • Studied at Georgia State University
  • Living in United States
  • Website https://kushagrasenw.wixsite.com/ksen
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About

My name is Kushagra Sen and I am an MSIS graduate student pursuing my degree in Big Data Analytics from Georgia State University and I’ve graduated in December 2020. . I have always been on the lookout for working in a customer-centric company and playing a key role in its growth and success by leveraging data around us!

A little bit about me:
I carry more than 3 years of work experience (focused in data analytics) in the Business operations, Ad-tech, Risk/Compliance, and Social Network domain and, I recently worked as a Data Scientist at IMVU. During my professional crusade and master’s journey I have obtained in-depth experience on how to work cross-functionally with various Machine learning, Product Management and Software Development teams. I have developed end-to-end skills from the identification of data requirements to the incorporation of analytics and machine learning technologies right from experimentation to production pipelines.

I am thoroughly exposed to machine learning and parallel processing ecosystems like Apache Spark, Hive, Presto, AWS along with a good hold in SQL, NoSQL, Python, and advanced MS Excel. I am experienced in building data pipelines to convert unstructured data into readable tabular formats and then visualize it by developing customized dashboards. I also have good experience in Digital Marketing Analytics while working at Media.net to optimize the multi-channel web traffic acquisition for a range of publishers in the USA. I was responsible for top-line growth, maintaining network quality and meeting advertiser goals.

While working at various firms, I have helped my team in achieving our business goals through my data analytics and engineering skills and, I am confident enough that I will be a good fit for your company. As I love to work in an agile environment, I went ahead and got certified as a Scrum Master with the Scrum Alliance, to enhance my project management skills.

Apart from my work, I love hiking and meditation. I am very eager to learn the upcoming new technologies, and I am confident about my quick grasping skills.
I am looking for opportunities in the data analytics domain and I can start in January 2021.

  • Experience

    IMVU - Data Scientist Intern
    • Partnered with C-level executives to gather requirements, define custom KPIs and perform ad-hoc analysis to drive technical product development and decision-making to improve the 3D chatting experience for 10 Million+ users.
    • Successfully migrated data sources & reports to Presto on AWS from on-premises Hive servers (~200 data sources).
    • Fine-tuned the featured products by 10%, by analyzing user buying trends on IMVU’s multi-tier shopping catalog.
    • Re-designed data pipelines using HiveQL & Presto which optimized the time to query data from base tables by ~8%.
    • Developed a detailed report of the platform-wise trend of promo-campaigns using Presto SQL and Tableau. This analysis helped the CRM team recognize that iOS platform gives a 20-25% better conversion rate during weekends.

    Vital 4 - Data Analyst NLP Intern
    • Leveraged python libraries to perform natural language processing for entity extraction from text documents. This optimized the minimum viable product to facilitate purposes like sentiment analysis, employee screening and KYC.
    • Automated web scrapping tasks using Selenium web driver and Python which slashed manual tasks by 2 hours/day.
    • Used SQL for extract data from incoming JSON files and convert them into readable tabular formats for analysis.

    Media.net - Campaign Manager – Decision Analytics
    • Built a team of 4 digital marketing analysts to provide monetization solutions through digital campaigns for tier-1 publishers in the USA and European market while maintaining a Y-o-Y growth of more than 40% for 5 quarters.
    • Created ad-click data stream on Google Big Query using MS SQL and Python. Developed a Tableau dashboard on top of it for tracking the ad-clicks on the publisher's websites. This was used for optimizing monetization metrics.
    • Conducted spam traffic analysis of the incoming clicks on our SERP's leading to a ~10% drop in the spam clicks sent to the upstream ad-providers in the Yahoo/Bing ad-network.

    Media.net - Analyst– Ad Platforms
    • Provided data-driven insights to the global sales team through ad-hoc analysis, presentations, and automated reports and dashboards, to optimize the customer acquisition funnel.
    • Performed A/B tests and executed strategies for content curation to achieve SEO/SEM goals and introduced 7 new verticals which helped in the overall revenue increase by 18%.
  • Projects

    COVID-19 Data Analysis Project | Python, Natural Language Processing, PCA, PySpark
    • Extracted COVID-19 research data using Python with Selenium WebDriver and loaded the JSON data to Spark. Used Spark SQL to gather KPIs and developed Tableau dashboards to get actionable insights.
    • Analyzed data to study location-wise trends and understand pandemic better, find answer to questions like symptoms, strategies to contain virus, current situation of world.
    • Implemented unsupervised state of the art NLP (BERT and Word2vec), simple descriptive statistics and PCA to find possible cures/vaccine for the virus.

    Twitter sentiment analysis of iPhone 11 series | R Programming, Ggplot2
    • Leveraged NLP and topic modelling (TF-IDF) to analyse the sentiments of over 35 thousand tweets, after the shopping season of 2019 ended. Developed useful plots showing various trends using Ggplot.
    • The analysis showed that overall contribution of positive tweets was of 52.8% while the negative sentiments had words such as “crack”, “iPhone care” and “brittle”.


    Graduate Admission Analysis and Prediction | NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn
    • Developed a machine learning model from scratch to predict the chances of a candidate receiving an admit from a college for their graduate studies based on their scores.
    • Used Decision Tree and Logistic Regression using cross-validation to predict admit chance with 98% accuracy.
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