Daniel James Walker, Ph.D.

Data Science - Data Visualization - Business Analytics - Machine Learning

May 2022 Dan Walker

Hello! My name is Dan, and I'm an experienced data scientist with nearly 5 years in the industry as of this writing. I have a probably uniquely diverse background in my education and professional experience, and I'm currently seeking my next opportunity. I spent 10 years in college and graduate school working in the field of conservation biology, studying and working to protect rare and endangered fish species. During my time in graduate school, I aggressively pursued my education in statistics, because I learned that you cannot publish anything in science unless you have the math skills to back it up. It was during this period in my graduate education that I was first exposed to the world of data science and business analytics, and I chose to become a data professional for my career. While I miss my days in conservation biology, I love writing code (especially in R and Python!) and making computers do what I want them to do. I get the greatest professional satisfaction when I'm able to translate a murky business 'what-if?' question into a data problem, and then design and implement the end-to-end pipeline necessary to generate robust, useful insights from seemingly impenetrable datasets. My passion remains with predictive analytics, but I have tons of experience in backend data engineering as well, and look forward to tackling the next big opportunity! Thanks for reading!

Ph.D. | University of Tennessee, Knoxville | 16 December 2017

• Major: Natural Resources Management, GPA 3.95

M.S. | University of Tennessee, Knoxville | 10 May 2014

• Major: Wildlife and Fisheries Science, GPA 4.0

B.S. | Appalachian State University | 08 May 2012

• Major: Ecology and Environmental Biology, GPA 3.85

Analytics

• Machine learning and statistics – R and Python, fluent in Tidyverse, caret, and scikit-learn. Favorite ML tools: RandomForests and xgboost, LSTM, unsupervised learning techniques
• Databases – extensive Oracle SQL experience, including automating database operations using DBMS scheduler and compiling Oracle Packages for global use; use SQLite for hobby projects; Postgresql for Airflow webserver backend
• Deep learning – extensive research in Long-Short Term Memory model design; developing custom Customer Lifetime Value to predict future customer value based on known customer attributes
• Certifications – AWS Certified Cloud Practitioner; working toward AWS Certified Machine Learning Specialist

Management

• R, Python, and deep learning reference for entire Business Analytics team – collaborated with junior team members to improve their analytics scripts for production environments
• Oversaw the development of several machine learning pipelines from initial requests from stakeholders to deployment and monitoring in production
• Supervised data collection and entry for quality assurance for multiple scientific research initiatives
• Maintained priority of safety for crews in varying field conditions including determining when the cost of organizing field research trips was outweighed by deteriorating weather conditions while on rivers and lakes

Professional Communication

• Multiple detailed technical reports regarding customer behavior, customer lifetime value predictions and interactive dashboards provided to multiple teams within JTV and C-Suite executives
• Primary author of two peer-reviewed scientific articles (one published Jan 2015, one published Sept 2016)
• Instructor of record for Environmental Science 111 courses at Tusculum College – classes of 10-20 students, majority of students non-traditional
• Ten presentations to scientific organization conferences (50+ audience members) since 2011

Data Science Manager | First Performance Corporation | March 2022 - May 2022

• Briefly managed an international team of data science for a FinTech startup before the company pivoted and eliminated the position

Senior Business Analyst | Jewelry Television | July 2018 – March 2022

• Implemented probabilistic method for estimating customer lifetime value, engineered an ensemble machine learning solution for predicting ‘at-risk’ customers, developed new index linking customer satisfaction survey responses to customer value estimates via machine learning

R Developer & Data Scientist | Trutta Environmental Solutions, Inc. | November 2017 – July 2018

• Ported large Excel based workflow into single easy-to-follow R script.

Adjunct lecturer | Tusculum College | January 2017 - December 2017

• Designed the syllabus, lecture, and assignment materials pursuant to the course requirements for Environmental Science 111 in the Graduate and Professional Studies evening program.