Data analyst with a degree in Applied Mathematics from Southern Methodist University. Experienced in efficiently querying large datasets in cloud-based data warehouses. I specialize in product analytics, focusing on analyzing user interaction (clickstream) data for both web and mobile applications. By working closely with cross-functional teams, I have designed and implemented new product features, defined KPIs, and conducted A/B tests to drive product improvements and optimize user experiences.
Work closely with members of the product team to improve the ShipStation.com user experience. Develop dashboards using Looker to display newly created first time use metrics. Design and analyze A/B tests with the goal of improving user experience, and reducing time to complete desired actions. Help to build the growth warehouse designed improve A/B testing workflow and turnaround time.
July 2023 - Current Date
Provide data insights and participate in data-driven meetings on a weekly basis with various stakeholders. Manage A/B tests, and deliver analysis. Leverage multiple massive and complex data sets to identify trends and patterns. Develop analytics calls with cross departmental teams for new app features. Initiate, design, and monitor reports, KPIs, and product tracking to drive growth. Design and develop dashboards using SQL and tableau for various teams and app features.
January 2022 - May 2023
Developed an internal tool using python to provide a map of GI clinics overlayed with customer location data. Performed quantitative analysis on medical claims data using Python and Excel. Developed utilization, savings, and census reports for internal and external stakeholders. Developed various python scripts to reduce reporting turnaround time. Developed dashboards using javascript, and visualizations using Python with Plotly. Extracted useful insights from healthcare data to provide savings to our customers.
December 2020 - December 2021
Data Analysis and Visualization Certificate
This bootcamp was an intensive and immersive program that provided me with a solid foundation in data analysis and visualization. Through hands-on projects and real-world datasets, I gained practical experience with a range of tools and techniques, including Python, SQL, Tableau, and machine learning. The bootcamp also provided valuable networking opportunities and connected me with a community of data professionals. Overall, it was a challenging but rewarding experience that helped me develop new skills and advance my career in data analytics
B.S. Applied Mathematics
My degree in applied mathematics has equipped me with a strong foundation in mathematical principles and problem-solving skills that I have applied to data analysis. Throughout my coursework, I learned how to use mathematical models and analytical techniques to solve complex problems and make data-driven decisions. Additionally, my degree program emphasized the importance of effective communication and collaboration, which has prepared me to work effectively in interdisciplinary teams. Overall, my applied math degree has been a valuable asset in my career, allowing me to approach challenges with a rigorous and logical mindset.
This web scraper is designed to pull the latest news and information about Mars directly from NASA's website. By leveraging powerful Python libraries like BeautifulSoup and Pandas, the scraper is able to extract and process large amounts of data in a matter of seconds. The resulting output is then beautifully displayed on an HTML page, making it easy for anyone to keep up with the latest Mars-related news and events. Not currently hosted.
Example View Code
This Jupyter Notebook allows the user to input two zipcodes, see them on a map generated via Plotly, and view the median home value and median income on a bar graph. It also computes the distance between the two zipcodes using the haversine formula which determines the great-circle distance between two points on a sphere given their longitudes and latitudes. All of the zipcode data comes from https://pypi.org/project/uszipcode/ This zipcode data could also be generated via an API call to openstreetmaps.
View Code
Tidy Tuesday is a weekly data project that encourages individuals to practice and improve their data wrangling and visualization skills. It was started by Thomas Mock on Twitter and quickly gained popularity within the data science and data visualization communities. Every Tuesday, a new dataset is shared on the Tidy Tuesday website or on the associated Twitter account (@tidy_tuesday). The datasets cover a wide range of topics and come from various sources. Participants are then encouraged to explore the data, clean it, analyze it, and create visualizations using tools like R, Python, or any other programming language of their choice.
Live Demo View Code