Jeff Hale

Head of Developer Education, Developer Advocate

• Created materials to educate data professionals about the benefits of Prefect for workflow orchestration
• Provided user feedback to product and development teams
• Taught in-person and remote courses to over 1,000 students with excellent reviews
• Presented talks at conferences such as PyData and ODSC

Lead Instructor, Data Science

• Taught over 70 different data science lessons to mid-career professionals on topics ranging from Python and SQL to data visualization and machine learning algorithms
• Developed course materials including lessons, hackathons, and projects
• Earned consistenly high marks from students and managers including Washington DC campus's first ever 100 NPS score
• Organized and hosted weekly speaker series with outside presenters on data science topics

Data Science Author

• Wrote over 70 blog posts that have been read over 1.2 million times
• Attracted over 18,000 Medium followers
• Designated a top Medium writer in the areas of Artificial Intelligence and Technology multiple times
• Writing featured in outlets such as Experfy, Data Elixir, Kaggle Newsletter, Dataquest Download, Python Weekly, O'Reilly Data Newsletter, and Data Science Weekly

Data Science Consultant

• Performed data analysis and data visualization for a membership organization
• Wrote data science blog posts for a high-growth tech startup
• Restrutured Airtable databases for a venture investment firm
• Wrote Python script matching data for a startup

Chief Operating Officer, Cofounder

• Oversaw IT, finances, and operations for e-commerce treadmill desk company
• Managed manufacturers and international supply chain logistics
• Performed customer segmentation and tracked marketing KPIs
• Built, managed, and A/B tested websites with Shopify, Cloudflare, and Google Analytics
• Created sales, inventory, and financial forecasts

Director of Finance and Operations

• Helped start law firm and managed finance, accounting, marketing, IT, and HR functions
• Performed decision analysis modeling case outcomes with Monte Carlo simulations

Stay at Home Dad

• Managed chaos as primary caregiver for two small children.

Director of Housing Development

• Modeled, evaluated, and managed development teams for multiple affordable housing projects
• Developed over $70 million and 1,000 units of affordable rental housing
• Wrote and presented grant and loan applications for housing developments resulting in over $8 million in awards

University of Arizona

• Net Impact, Merit-Based Academic Scholarship
• Taught Business Strategy, Human Resources Management, & Business Communication courses
• Studied a wide range of quantitative research methods and statistics in the context of marketing and organizational psychology for Master's degree in Management
• Studied decision making, marketing, finance, entrepreneurship, game theory business ethics

Bowling Green State University

• Magna Cum Laude, Honors Program, National Merit Scholarship, Phi Beta Kappa
• President, Habitat for Humanity; Vice President, Students for Quality Education
• Senior Computer Lab Coordinator, Residential Computing Connection

Certifications

• Google Cloud Certified Professional Data Engineer, 2019
• Microsoft Office Specialist: Excel 2010
• LEED AP, USGBC
• Certified Housing Development Finance Professional, National Development Council
• Completed many data science and technology online courses

Interactive Streamlit app to visualize COVID-19 case data in US counties using pandas, Plotly, and Streamlit.

A Python package for interacting with the libraries.io API to subscribe to open source project updates and get information about packages and repos.

Interactive Streamlit app that shows the code and output for popular plots from six different Python plotting libraries.

Used requests, BeautifulSoup, pandas, and seaborn to scrape, explore, and visualize New Belgium beer ratings. Tableau visualization here.

Blog Post Topics

• Docker
• Kubernetes
• Streamlit
• Tableau
• Dealing with categorical data types
• Scaling data
• Analysis of deep learning framework popularity
• Where to use GPUs in the cloud
• How to get data from APIs
• Where to find data
• Airtable
• Scikit-learn library updates
• Pandas library updates
• Speeding up your code
• Regression evaluation metrics
• Plotly
• Bash commands
• Building a Python package
• Git basics
• Python file system commands
• Pandas memory management
• NumPy arrays
• Logistic regression solvers in Scikit-learn
• Sorting speeds across Python libraries
• PostgreSQL booleans
• Writing tools
• Google Cloud Platform data engineer certification
• Classification evaluation metrics
• Deep learning image classification
• Creating docs
• Analysis of terms in data job listings