Data Information Technology
Resume:
LARISA MACHADO
******.*******@*****.***
SUMMARY:
Extensive (4+ years) experience in analytics space with a deep understanding of analytical methodologies and techniques
Experience in working with teams and engagements to solve business problems using data analytics
End-to-end experience in designing and deploying data visualization
Well versed in understanding, analyzing and applying algorithms and regression on data
Master’s degree in Computer Science (Analytics)
SKILLS: Languages: SQL, R, Python (NumPy, Pandas, SciPy, Scikit learn, Matplotlib), SAS, HTML, C, C++, Java, Linux
Methodologies: KNN, k-means, Decision trees, CART, Principal Component Analysis, Logistic regression, MANOVA, ANOVA, Multiple regression Analysis, Factor Analysis
Database Systems: RedShift, MySQL, SQL-Server
Visualization Tools: Tableau, Power BI
Software/Tools: GitHub, SQL-Workbench, AWS, Atom, Excel, PowerPoint, Eclipse
EDUCATION: Stevens Institute of Technology, Hoboken, NJ
Master of Science, Computer Science May 2017
Mumbai University, Mumbai, India
Master of Science, Information Technology May 2013
Bachelor of Science, Information Technology May 2011
PROJECT: RedShift Migration May-June 2017
Migrated in-house data to RedShift, performed quality checks on data to ensure format and correctness. Built a reporting layer (Tableau) on top of RedShift.
Built reports like what if analysis, LODs, Dual axis, Time series graph and Pie charts on Tableau desktop using Yelp dataset.
Environment: SQL workbench, Tableau 9, AWS Redshift
EXPERIENCE: United Nations Headquarters – Data Analyst November 2017 to February 2018
Worked on merging datasets from different sources using Tableau extracts and data blending for further visualization on final data set
Created interactive dashboards using filters, drill down and drop down menu with functionalities like dual axis, bar graphs, time series chart, bubble charts, pie graphs, line charts and heat maps
Connected Tableau server to publish dashboards and maintained accessibility to users
Involved in gathering data, merging and transforming into meaningful insights - creating pivot table, Vlookup, Hlookup and VBA in excel.
Generated SQL queries to document in user guide for future assistance to personnel
Created database in MS Access and generated Queries, Reports and forms.
Environment: Tableau 10, MS SQL, MS Access, MS excel
V.V Engineering – Associate Business Analyst July 2013 to November 2015
Performed customer segmentation depending on purchase behavior
Determined the minimum stock and profit margin by building a model that can group items into categories ‘fast moving and slow moving’ using k-means clustering
Gathered the requirements, designed and developed new reports (Gantt charts, bar graphs, bullet graphs) and enhanced existing reports and capabilities in alignment with business needs
Designed new data sources for developing analytical reports from multiple data sources like Microsoft SQL Server, Microsoft Access and other flat files
Used VLookup, HLookup and pivot tables for quick summary reports
Involved in developing UI and synchronizing Crystal reports with SQL server for a complete Invoice Application
Environment: MS Access, SQL Server, Visual Basics, Crystal Reports, MS Excel
SERVER WorldWide - Business Analyst August 2011 to April 2013
Predicted customers preference based on order history to maximize sales efficiency by developing forecasting model
Analyzed and summarized customer satisfaction survey data and produced yearly reports
Generated Visualization reports – timeline charts, Pivot charts and pie graphs
Created a data model for Sales data in MySQL DB
Created stored procedures and utilities to manage relational and dimensional data
Environment: MySQL, MS Excel
ACADEMIC Stevens Institute of Technology, Hoboken, NJ
PROJECTS: Revenge or Repent
Extracted, interpreted and analyzed data to identify key characteristics of an offender and transform raw data into meaningful information.
Created a classification model in R to predict if offender will be re-admitted to prison or not within 3 years of release from prison using KNN, Decision tree and random forest algorithms using dataset from https://www.data.gov.
Contributing factors of Vehicles collisions
Performed data filtering, data cleansing and data encoding.
Developed a regression model to predict contributing factors of collisions caused by motor vehicles in boroughs of New York using Logistic regression on dataset from opendata.cityofnewyork.us using SAS.
Analysis of Uber Trips
Developed a Business Dimension model on kaggle’s dataset for Uber and compared Uber trips and yellow taxi trips in outer boroughs of NY to conclude Uber are taking away trips from yellow taxis.
Visualized results in time series, bar chart and bubble chart using Tableau.
Yelp Anomalies
Established a model in Python to identify significant changes in average rating, through a one-sample t test, and then provided a brief summary of customer’s text for those periods using Yelp Businesses and Reviews files.
Created a bar chart representing the mean ratings per quarter and highlighted anomaly periods
Web Scraping
Implemented Web Scraping in Python using the beautiful soup library to search for similarity among the text from the page.
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