Data Information Security

PALAK KANSARA

Address: Riverside, CA ***** Email: *******.*@************.*** Mob: +1-857-***-**** LinkedIn

EDUCATION

Northeastern University, Boston September 2018 – April 2020

Candidate for Master of Science in Analytics

Relevant Courses: Probability and Statistics Predictive Analytics Data Mining Applications Data Management and Big Data Enterprise Analytics Risk Management Analytics Communication and Visualization in Data Analytics Predictive Analytics

Gujarat Technological University, Gujarat, (India) August 2012 – May 2016

Bachelor’s in computer science and engineering

Relevant Courses: Web Development Data Mining Operating System Information Security

TECHNICAL SKILLS

Data Analysis and Reporting Tools: MS Excel SQL Tableau MS Power BI Hadoop ERP AWS

Programming Languages: R ( ggplot2 tm tidyverse Rshiny ) HTML CSS Javascript GIT

Machine Learning: Linear Regression Logistic Regression Naïve-Bayes Classifier Random Forest Decision Trees Ensemble learning (XGBoost) Natural Language Processing (NLP) K nearest Neighbour

Visualization Tools: Tableau MS Excel Plotly Ggplot2 R-shiny

WORK EXPERIENCE

PMET Industries – Vadodara, Gujarat August 2017 – June 2018

Business Analyst

Identified possible solutions for business problems and made continuous improvement activities by analyzing and documenting business requirements, drafting project plans, and preparing risk logs.

Initiated requirement gathering sessions and facilitated reviews throughout the software development life cycle with agile.

Developed dashboard using Python, Tableau and SQL for checking the performance of the products and reported the values enabled.

Led budget research analysis to develop cost metrics which leaded to a 20% increase in funding.

Developed advance Tableau dashboards to provide clear visualizations to track and improve customer units KPI by 13%.

Implemented numerous data collection systems utilizing MS ACCESS, SharePoint and Outlook for reporting and analytics.

Helped with drawing different work/data flow and timeline for various projects with Creating Management layouts in Excel and utilized

Macros (VBA) to consequently produce Periodic status reports.

Assisted with the end to end project management of reporting and ETL development projects within the team.

Generated multiple excel based reports using VLOOKUP, Pivot tables, Visio and Charts to support ad-hoc needs of the operations organization and provided visibility to leadership to help take crucial financial decisions for improving the sales of the products.

Collabera – Vadodara, Gujarat June 2016 – July 2017

Technical Analyst

Acted as a liaison between onsite and offsite as well as for cross-functional teams like Sales, Finance, development and BI.

Did data collection and manipulation from various recruiting sites for finding candidates for a requirement from clients

Prepared reports and logs for the recruited candidates which for a project requirement on weekly and monthly basis.

Communicated with the clients as well as account managers regularly for project requirements and weekly targets.

Executed, leaded and trained a team for full recruitment life cycle from extraction of data in SQL till creating interactive visualizations in tableau for clients and senior management.

Used A/B tests to improve recruitment by 7%.

Worked on MS Excel for data modelling tools, macros, formatting and using different functions to manipulate the raw data of the candidates, Clients and requirements.

ACADEMIC PROJECTS

Northeastern University, Boston September 2018 – April 2020

Boston Residential Property Analysis Technologies: R Tableau SQL

Converted Property Assessment data into actionable insights and predicted total assessed property value for residents

Leveraged data visualization and compared statistics to select the residential investments for families

House Price Prediction: Technologies Used: Python AWS

Performed regression analysis using gradient boosting to predict house prices on Kaggle House Price Competition. https://www.kaggle.com/c/house-prices-advanced-regression-techniques

Sentiment Analysis on US Airline Twitter Dataset Technologies: Python scikit-learn pandas numpy

Analyzed tweets, extracted top words of Positive, Negative and Neutral sentiments and created word-cloud. Built multinomial classifier using n-gram features that predicts the sentiment class from tweets.

Contact this candidate