Christopher Havenstein

Location: Midland, Texas

Integrated Operations Data Science Analyst at ConocoPhillips

What have you been up to since completing the program?

Since completing the program, I have continued to apply the data science skills I have learned at SMU in my current job at ConocoPhillips. While I was in the program, I was promoted to my current role as an integrated operations data science analyst. Also, I work as a machine learning teaching assistant for SMU teaching Master of Science in Data Science students Python machine learning skills and related concepts.

How have you implemented the skills and tools learned in the program at your current job?

I have already performed a study to analyze well failures with one of our field location’s data by using random survival forests. Using this model, I was able to predict failures at this field with approximately 75 percent accuracy while also providing operational recommendations using available features with global and local model interpretability. Currently, I am a member of a cross-functional team to predict well failures with statistical machine learning by using a variety of available data sources.

How has earning a master’s in data science helped you in your career?

I have been able to teach others data science and machine learning concepts, speak confidently about related subjects and perform prescriptive analytics at a level I could not previously do.

Did you utilize any of SMU’s career services during your time as a student?

I was fortunate to be promoted during my time as a student in my current company. Therefore, I did not use SMU’s career services to locate a job as a student.

Did you have a favorite class or project in the program?

My favorite project in the program was my machine learning final project where I trained an artificial intelligence agent to play “Ms. Pac-Man. To do this, I learned about deep reinforcement learning and trained the AI agent for about a week with TensorFlow GPU and Keras. The agent learned from different image training data by playing many games over the course of 30 million moves. As a result, while the AI player was not fantastic, it could play “Ms. Pac-Man” and occasionally beat a level.

What is the most valuable thing you learned while in the program?

I have learned how to quickly research and confidently implement statistics and machine learning methods in a variety of programming languages to solve business problems.

What advice do you have for currently enrolled students?

Do not be afraid to try statistics or machine learning methods that appear very complex or you perceive to be very hard. Give yourself enough time to learn and to fail. School is a relatively safe place to fail. If you do fail to deploy such complex methods, communicate early to your professors and share about the journey. That journey may serve as a tremendous kickoff point for other students who can learn from your experiences.

Where would you like to see yourself and your career in 10 years?

I would like to lead a team of data scientists and share what I have learned along my career with others who are beginning their own data science journey.