Rachel Windsor

Background

About Rachel Windsor

A highly analytical, innovative and detail-oriented problem-solver: help business/organizations to increase growth or reduce cost by consulting with management/stakeholders to identify business needs/problems by gathering information, analyzing data and providing actionable recommendations/solutions from data insights.Skills and experiences include:* Design surveys using Google forms, Qualtrics, and SurveyMonkey (with applied psychometrics)* Conduct research with hypothesis-testing, A/B testing* SPSS syntax: t-test, ANOVA, correlation, linear regression, reliability (Cronbach's alpha), factor analysis * Data Mining & Analytics (R): Linear Regression, Logistic Regression, Classification and Regression Tree (CART), k-Nearest Neighbors algorithm (k-NN), Sentiment Analysis, Cluster Analysis, Association Rule, Vector Support Machine (SVM), Random (Decision) Forests* Data Visualization: ggplot2; rattle (i.e, Graphical User Interface) to represent analyses* Visual design (e.g, Adobe Creative Cloud: Spark)* Employment Laws (more specifically, EEOC laws and regulations and California's employment-related laws and regulations)- Strong interests in research, technology, quantitative analysis, and machine learning- Experience in interpreting data insights for different stakeholders (technical and non-technical audiences) through storytelling so as to address organizational questions and needs- Highly detail-oriented and passionate about research-based applied psychology and data-driven strategies to solve business problems.