Vrushali Bandale

Studied at Northeastern University
Living in United States

About

Graduate student at Northeastern University, Boston MA with interest in Data Analytics, Data Science, Business Analytics, and Data Engineering

Strong skills include business etiquette and professional attributes. I believe in directing my Individual accomplishment toward organizational objectives.

I am actively seeking opportunities that delve into logic and data analysis and insight of machine learning which would better align me towards my goal.

Skill Set:
• ML Techniques: Linear Regression, Logistic Regression, Support Vector Machines, Decision Tree, Gradient Boosting, K-Nearest Neighbors, Random Forest
• Database: MySQL, Microsoft SQL Server, Oracle, PostgreSQL
• Tools: SSIS, Microsoft Azure, Tableau, PowerBI, Talend, Excel (Power Pivot, VLOOKUP)
• Languages: Python, Java, C#, HTML, CSS, Javascript, SQL, PL/SQL
• Source Control: Git, BitBucket
• Libraries: NumPy, Pandas, Sky kit learn, Seaborn, Matplotlib, PySpark
• Specialties: Data Analysis and Visualizations, Data Modelling, Statistical Analysis
• Business Analysis: PowerPoint, JIRA, Agile Project Management, Scrum, SDLC, GIT

Experience
• Developed an enterprise application using business process management suite Agilewiz
• Coordinated end to end development process of ERP System with client
• Programmed critical tasks of Educational Management, HR Management, Travel Module successfully by using C#
• Built data models using complex SQL Queries, Stored Procedures and Functions for query optimization
• Coordinated incident and problem management within teams across different locations
• Mentored new project members by demonstrating the software development life cycle of the system and resolving their queries and decreased the onboard time
• Expertise in preparing business cases, sequence diagrams, use cases, activity diagram in MS Visio
• Performed data analysis to ensure data accuracy (business and technical compliance)
Projects
Performed Machine Learning algorithms like Kalman filter, Long Short Term Memory, Linear Regression, Random Forest on Apple Stock Data.
Worked on trading strategies to buy or sell the Apple Stocks by using Bollinger Bands