Developing effective data scientists
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The document discusses the essential skills and experiences for developing effective data scientists, emphasizing strong communication, coding practices, and exposure to diverse datasets. It includes advice from various data scientists on the importance of curiosity and interdisciplinary learning. Additionally, it provides actionable to-do's for both students and teachers to enhance data science education.
Developing effective data scientists
- 1. Developing data scientists Erin Shellman PhD Data Science Kick-off University of Michigan October 6, 2015 effective
- 2. MS in Biostatistics ’08 PhD in Bioinformatics ‘12 …and an alum! I’m Erin and I’m a data scientist.
- 4. 1. Present your work 2. Blog 3. Teach others Student’s t0-do:
- 5. Center coursework on presentation and communication Teacher’s t0-do:
- 6. data scientists write high-quality code. effective
- 7. –Sarah Guido, Data Scientist @ Bitly and UM alum The single most useful thing I learned in grad school was how to work with data in Python.
- 8. –Trey Causey, Data Scientist @ ChefSteps, @4thdownbot I wish there had been more emphasis on real data/messy data/getting my own data/cleaning data.
- 9. 1. Develop deep expertise in a programming language 2. Adopt good coding practices now Student’s t0-do:
- 10. 1. Expose students to a variety of datasets 2. Focus on applications Teacher’s t0-do:
- 11. data scientists are curious, life-long learners. effective
- 12. –Wendy Grus, Technical Data Analyst @ Inrix and UM alum LEARN MORE CODING AND STATISTICS. Meet other people working on data sets not in your field. Learn something not in your field. Don't sit in a box staring at your thesis project.
- 13. –Amanda Casari, Senior Data Scientist @ Concur I took Naval Criminal Law & international relations. It was hard to stay awake. By comparison, I looked forward to vector calculus and loved Matlab. Lesson: Don't be afraid to explore your options while you are still on the track of figuring out what comes next.
- 14. –James Pestrak, Senior Data Scientist @ Nordstrom Boundaries between disciplines are becoming less-defined. There are general, powerful patterns of thinking that apply to many disciplines. A good way to become aware of these patterns is to broaden exposure to disciplines.
- 15. 1. Pursue academic interests outside your discipline 2. Go to meet-ups! Student’s t0-do:
- 16. 1. Teach with diverse datasets 2. Illustrate parallels between disciplines Teacher’s t0-do:
- 17. Big ups to these data scientists effective Amanda Casari Trey Causey Wendy Grus Sarah Guido James Pestrak