- Authored technical books about machine learning, data science, and algorithms.
- Clients: No Starch Press and Packt.
Bradford Tuckfield
About
Bradford Tuckfield is a data scientist with skills in statistics, programming, and machine learning. He previously worked as a senior manager of data science at American Express Global Business Travel, where he designed and coded clustering methods for an enterprise product. At Charles Schwab, he worked on model calibration and optimization, chatbots, NLP, and data analysis. Bradford is also an instructor and technical book author about data science, machine learning, and algorithms.
Employment
- Taught data science, NLP, coding, analytics, finance, and economics programs.
- Created videos and full courses for Udacity on machine learning, AWS, and DevOps.
- Clients: ViaX, Udacity, and Great Learning.
- Worked on model calibration and optimization, chatbots, NLP, data analysis, and machine learning.
- Automated lead generation leading to over $200 million net new asset acquisition.
- Designed and coded clustering methods for an enterprise product earning $60,000 per customer.
- Forecasted client attrition and customer volume, enabling over 10% call center cost savings.
- Performed sentiment analysis and NLP for proactive customer care.
- Designed and implemented fuzzy matching methods for transactions and peer benchmarking.
- Conducted time-series analysis of sales volumes for econometric measurement of a new product’s impact.
- Automated detection of fraudulent and erroneous transactions.
- Led the data science, data engineering, and application development teams.
- Developed a business intelligence chatbot.
- Created a monitoring system to enable cryptocurrency arbitrage.
- Designed and built recommendation systems for real estate financing decisions and customer prospecting.
- Worked with data projects end to end, including ETL's, data cleaning, back-end analysis, web frontend development, deploying internally, and training users.
- Built interactive web applications using R, Shiny, JavaScript, and D3 for internal use.
- Wrote web scraping scripts for US Treasury data and public real estate data using R and Python.
- Predicted revenue using regressions and machine learning techniques.
- Trained developers in R programming and statistical modeling.