My fascination with data science and analytics started as an undergraduate when one of my professors approached me about a research position in her affective science lab. I instantly fell in love with the quantitative nature of the work, taught myself to code, and started taking math and computer science courses to supplement my psychology major.This early interest has since developed into a gratifying career, where I've had the opportunity to contribute to projects in machine learning, artificial intelligence, and traditional business intelligence and analytics. As a versatile data professional, I've cultivated a robust proficiency in analytics, machine learning, and AI, reinforced by a solid understanding of ETL processes and workflows. From my college days using MATLAB and SPSS, I have adapted to the evolution of tools and technologies, now primarily working with Azure, SQL, Alteryx, Python, and visualization tools like Power BI and Tableau.Currently, I work as a Data Scientist at Thrivent, and I recently completed Springboard’s Data Science Career Track bootcamp with the goal of furthering my skills and zeroing my broad data background into a more data science focused approach. I’m excited to bring the breadth of knowledge and technical experience I’ve gained from my experience working as a data professional to new projects and contribute to thinking critically and solving the toughest problems facing the business. I love to be challenged, and I’m excited about the future of data science, embracing both the remarkable opportunities and unique challenges that the advancement of artificial intelligence will bring.I’m always ready to talk data and make new connections. Feel free to reach out to connect!Skills: AI, Alteryx, Algorithms, Business Intelligence, Dashboards, Data Analysis, Data Cleansing, Data Collection, Data Engineering, Data Science, Data Visualization, Data Wrangling, ETL Processes and Workflows, Generative AI, Git, Hadoop, Machine Learning, Microsoft Azure, Microsoft Power BI, MySQL, Natural Language Processing (NLP), Pipelines, Predictive Modeling, PySpark, Python, R, Regression Analysis, Relational Databases, SQL, Statistical Modeling, Statistics, Supervised Learning, Tableau, Time Series Analysis, Unstructured Data, Unsupervised Learning