Anirudh Govindaraj Jaichandran

813-***-**** adoqf8@r.postjobfree.com LinkedIn 12806 varsity club court, Tampa, FL PROFILE SUMMARY

MS Candidate currently pursuing Business Analytics and Information systems with a strong foundation in computer science and engineering. Seeking full time opportunities starting December 2021. EDUCATION

University of South Florida (USF), Tampa, FL Expected Graduation: December 2021 Master of Science in Business Analytics and Information Systems PSG College of Technology, Coimbatore, India July 2015- May 2019 Bachelor of Engineering in Computer Science

SKILLS

Statistical Inference: A/B Testing, Hypothesis Testing, Correlation, Confidence Interval, Regression, Probability. Data Engineering: Data extraction, manipulation and database management, MySQL, Oracle, Apache Spark, Hive, Hadoop.

Machine Learning: Classification, Regression, Clustering, Dimensionality Reduction, Deep Learning, NLP. Programming Languages: Python (pandas, NumPy, matplotlib, scikit-learn, tensorflow, seaborn, BeautifulSoup, keras, regex, nltk), R, SAS, PySpark, C++, C#, Java, PHP, HTML, CSS, Typescirpt, Javascript. BI & Analytical Tools: PowerBI, Tableau, Microsoft Excel, SAS Enterprise Miner, Azure ML Studio. Tools & Technologies: Anaconda, Jupyter Notebook, R Studio, SAS studio, Microsoft visual studio, Azure ML studio, Microsoft Office, XAMPP.

Soft Skills: Problem Solving, Analytical Thinking, Communication and Presentation skills. Relevant Coursework: Data Mining, Data Science Programming, Text Analytics, Big Data, Statistical Programming for Business Analytics, Analytical Methods for Business, Data Visualization, Advanced Database Management Systems, Software Testing, Information Security & Risk Management, Enterprise Information System Management. ACADEMIC PROJECTS

Restaurant Review Analysis on Yelp

• Scrapped restaurant reviews from yelp.com and analyzed reviews to understand customer sentiment, likes and dislikes.

• Performed Aspect Based Sentiment Analysis based on aspects such as food, ambiance, service and price.

• Used Wordnet and Word2Vec to extract and tag reviews pertaining to each attribute.

• Built a linear regression model to analyse the impact of each attribute on a patron’s overall rating and regressed the computed score against the overall rating to estimate the effects.

• Created a PowerBI dashboard that provides insights on popular dishes, customers opinion about ambiance, service and pricing for the restaurants.

Telco Customer Churn Analysis

• Lead team of four to analyze customer churn.

• Created an end-to-end machine learning pipeline using Apache Spark in databricks to perform analysis

• Used SparkSQL to analyze, manipulate data and toPandas to build visualizations and transformer package in SparkML for feature engineering and built various models such as logistic regression, random forest, decision tree and xgboost and evaluated the performance of models using binary classification metrics. Multi class classification of customer service queries

• Classify customer queries into seven topics such as “Shipping”, “Product Availability”, “Returns”, etc.

• Performed pre-processing of queries and feature engineering using TF-IDF, word2vec and Doc2vec.

• Built a multi-class classifier that can automatically classify new incoming queries into one of the seven topics using classifiers such as KNN, Random Forest and Deep Neural Network. Statistical Analysis on Video Game Sales

• Performed descriptive statistical analysis on the video game sales data.

• Performed Linear Regression Analysis on the sales of video games based on various factors such as critic rating, user rating, genre, publisher and platform and tried to determine which factors have high impact on the customer’s buying criteria.

• Checked to see if the final model satisfies the assumptions of Linear Regression. Disaster Tweet Analysis

• Used NLP to analyze tweets that are about ‘actual’ disasters.

• Performed pre-processing (tokenizer, stop word removal, lemmatization, etc) of tweets and built machine learning classification models such as KNN, XGBOOST, Naïve Bayes, Logistic Regression and SVC to classify the tweets. PROFESSIONAL EXPERIENCE

Aagnia Technologies, Coimbatore, India Application Developer Intern Dec 2018 – April 2019

• Implemented the design and functionalities of League-iv, a web-based application, using responsive web design and tested for its scalability and performance across different devices.

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