Manas Kore Resume
Analytical and highly skilled professional with hands-on experience in working with stakeholders to elicit, analyze, visualize, and validate data and solutions requirements to meet business needs. Experienced in delivering provision of strategic insight, interpretation of data, data mining, visualizing datasets, and production of comprehensive reports. Collaborative communicator focused on building client relationship to obtain comprehensive understanding of data to establish detail business requirements.
Data & Business Analysis
Adept at developing and maintaining of company’s data analytic platform enabling business units to make decisions and achieve better outcomes.
Skilled in gathering and interpreting data through market analysis to provide optimal solutions.
Excel at optimizing statistical efficiency and quality via development and implementation of improved data base, data collection system, data analytics, and other data related strategies. Data Visualization
Expert in data warehousing, ETL database functionality, data modelling and effectively handle multiple work assignments.
Proven success at analyzing small and large data sets to discover patterns and deliver meaningful insights.
Skilled in managing agile processes to assist in completion projects by utilizing effective techniques such as A/B testing. Ability to coordinate with cross-functional work teams toward task completion.
Programming Language: Python, R, SQL, Java, HTML5, CSS3
Cloud Services: AWS (EC2, S3), Google Cloud Platform, Azure
DataBase: MySQL, Microsoft SSMS, MongoDB, Postgres SQL, Oracle
Visualization & BI Tools: Tableau, Excel, Visio, Google analytics, Power BI, JMP, Jira, Salesforce
Malloy Group, California June 2020 – Aug 2020
Supported team aspects, collaborative approach, and innovative products by implementing e-learning platform policies for HP.
Organized an agile environment to manage e-learning platform strategies for HP.
Contributed to the success of group of 30 plus people and delivered e-learning platform strategies.
Gathered and analyzed data from 10 plus meetings and developed plans according to requirements of stakeholders.
Evaluated input and priorities of client’s primary stakeholders for developing e-learning strategies.
Conducted interviews to gain input and information about client’s primary stakeholder’s preferences.
Managed synchronous e-learning activities by utilizing design-based thinking approach and data from stakeholders meeting.
University of San Francisco, CaliforniaOct 2019 – June 2020
Utilized pivotal tables and formulas (v-lookup and others) for summarizing and organizing inventory and course data.
Maintained data cleaning and analysis by using pivotal tables and formulas in MS Excel.
Conducted feedback surveys on Qualtrics to collect data and evaluated students input about courses.
Improved decision making by creating data visionary reports through feedback surveys.
Trained over 500+ students on accessing, viewing, editing, and searching patient data.
Operated and managed $200000 worth of Laerdal products (Sim Man 3G).
Managed and maintained nursing patient data quality on Lippincott DocuCare.
Streamlined live A/V simulation processes by working on Laerdal products in healthcare field.
BST Eltromat India Pvt Ltd, IndiaMay 2017 – May 2019
Built data pipeline to enable the flow of data from an application to a data warehouse.
Evaluated market situations and reported on sales datasets by using visually effective dashboard in Excel and Tableau.
Evaluated performance and market analysis to determine sales.
Developed reports by gathering and organizing operational data on existing customers, competitors, and relevant products in market.
Increased worked efficiency by 13% through IT techniques optimization.
Boosted product sales over 8% by continually monitoring sale.
Credit Card Fraud Detection (EDA, KNN, Logistic Regression, SVM, Random Forest)
Provided safety for financial institutions, banks, and customers to identify frauds in credit card transactions. Uncovered fraud activities by building and comparing four different machine learning models. Collected dataset from Kaggle, imported required python libraries, performed EDA, pre-processed data, trained ML models using KNN, logistic regression, SVM & Random Forest for classifying the validity of credit card transactions. Compared all models using confusion matrix to determine that KNN was best suited for this use case.
Stock Market Analysis (pandas, NumPy, matplotlib, seaborn, LSTM)
Delivered intelligence, visualizing various stock aspects, and predicting future stock prices by analyzing stock market data. Used pandas & NumPy for analyzing data, matplotlib & seaborn for creating data visualizations and LSTM for predicting future stock prices based on the stock’s previous performance history.
Wine Quality Prediction (Python, Tableau)
Predicted the quality of wine based on its chemical composition to disapprove a popular hypothesis, that the quality of wine is primarily depended on its age, and presented results using data visualizations from Tableau. Worked in Anaconda Navigator with Python as a primary language utilizing popular python libraries like Pandas, NumPy, SciPy, Matplotlib, Seaborn, Scikit Learn & Plotly for creating ML models using KNN and Random Forest. Implemented ML models to predict the quality of wine with an accuracy of 86% for KNN and 89% for Random Forest.
California Wildfire Database System (Waterfall Model, MYSQL, AWS)
Worked in a group of four, to build a database of the most accurate record of each massive wildfire in California by following waterfall methodology to run predictive analytics and build forecasting models for improving planning and prevention tactics for future wildfires. Created DB using MYSQL Workbench and established a connection with AWS RDS while leveraging workbench tools. Constructed ER diagrams, conceptual & logical schema, and developed the DDL scripts required for creating database.
Train Reservation System (Agile, System Modeling & Design, UML, Lucid Charts)
Worked in an agile setting to deliver a comprehensive model and a prototype mockup for a Train Reservation System. Measured economic and operational feasibility required for system to develop use-cases, domain class, and system models.
Election Prediction Using Deep Learning & Opinion Mining (Sentiment Analysis, Naive Bayes, Porter Stemming, Agile)
Led and collaborated with a team of 4 people for developing a web app that predicts the likelihood of a political party to win an election based on people’s opinion, using text classification algorithms like Naive Bayes & Porter Stemming. Presented results and published findings in a paper (IOSR Engineering Journal, Volume 10; PP 84-86).
Master of Science in Information System | University Of San Francisco, California (GPA: 3.80) 2020
Bachelor of Engineering in Information Technology | University of Mumbai, India 2018
Tableau for Data Science, 2020 Complete Python Bootcamp from Udemy