Data Analyst Python

Apoorva Shadaksharappa

+1-408-***-**** San Jose, CA-95113 *******.**************@****.*** https://www.linkedin.com/in/apoorva-s2/ EDUCATION:

Master of Science in Computer Engineering San Jose State University May 2020 Bachelor of Engineering Visvesvaraya Technological University, India June 2015 TECHNICAL SKILLS:

• Technologies: C, C++, Python,Perl, AWS, VBA, SQL, NoSQL, HTML5, CSS3, JavaScript, Angular JS, jQuery, AJAX, Node.js, MongoDB.

• Tools: Jupyter Notebook, Visual Studio Code, Power BI, Tableau, Microsoft Excel, JIRA, SEEP, Github.

• Data Science/Analytical Skills: Statistics, Exploratory Data Analysis, Web Scarping, ETL, Hypothesis testing, Regression, Classification, Recommender Systems, Natural Language Processing, Neural Networks (CNN, RNN, DNN).

• Big Data: Apache Hadoop, Hive.

• Python Libraries/Framework for Data Science: NumPy, Pandas, matplotlib, Scikit, TensorFlow, Scipy, OpenCV, Keras.

PROFESSIONAL EXPERIENCE:

Data Analyst QA Intern, Wiser Solutions, San Mateo, CA Dec 2019 – May2020

• Build regular expressions in conjunction with the extract flags to extract all required data values from any web page, JSON, APIs and write scripts to manipulate data.

• Ensured data quality and integrity of retail price data extracted from multiple marketplaces to help increase revenue and improve marketing effectiveness for eCommerce clients.

• Validated multiple hypotheses on price violations, based on the competitor’s retail price data, to generate insights and enabled eCommerce clients to make pivotal decisions on their Minimum Advertised Price (MAP) using MS Excel.

• Developed tableau reports for the analytical datasets created using SQL and Python to interpret clients’ pricing behavior across eCommerce platforms.

Graduate Research Assistant, San Jose State University, San Jose, CA May 2019 – Sept 2019

• Worked on Reinforcement Learning smart scheduler design for cluster tools to improve the current throughput for Lam Research.

• Collaborated with the design team at Lam Research in the design of effective technical solutions aimed to achieve robustness at system software architectural level. Data Analyst, Tech Mahindra, Bengaluru, India. Aug 2015 – Feb 2018

• Designed statistical models (Linear regression, Logistic regression, clustering, decision tree, Random Forest models) to understand the relationship strength of law firm and its attorneys with their clients.

• Worked on Data mining & Cleaning, Exploratory Data analysis, Feature analysis, Prediction Modeling and Data Visualization using Python.

• Experience in executing analysis using tools such as SQL, Python, Excel, and Tableau.

• Designed and developed reports, scorecards, KPI dashboards, A/B testing.

• Experience in building, maintaining customized interactive dashboard, dynamic KPI reports and effective visualization dashboards using Tableau/Excel to identify gaps and key metrics. PROJECTS:

Social Relationship Recommendation System Jun 2019 – Aug 2019

• Built an UI to recommend followers on Twitter by analyzing hashtags and tags in the user tweets data. The dataset was taken from Twitter developer API with groups of accounts and users, tweets and replies using developer tokens. Stock Market Prediction Using Natural Language Processing Jun 2019 – Aug 2019

• Designed a Machine learning model that makes accurate predictions in stock market trends. Employs Natural Language Processing on current world affairs by learning the relationship between world news and market behavior. Restaurant reviews based on Yelp Data Feb 2019 – Mar 2019

• Built a Yelp review classifier for a new ranking scheme using multiclass classification to classify the review data set provided by Yelp using Scikit Learn python library. Augmented Image/Scene captioning system Oct 2018 – Dec 2018

• Designed an interactive system that takes voice inputs from the user as a command and detects the scene and guide according to the commands to assist people using Machine Learning. Web UI for Harvard Course data visualization Mar 2018 – May 2018

• Designed and developed a web application to help the users in predictive, descriptive and perspective analysis of Harvard course data visualization.

• The application provides decision making aid based on various Key Performance Indicators (KPIs). Tech Stack: Mongo DB Express React Node JS React-google charts UI Design Patterns

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