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So You Want to Work in Tech: How Do You Make the Leap?

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Non-Academic Careers for Quantitative Social Scientists

Part of the book series: Texts in Quantitative Political Analysis ((TQPA))

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Abstract

In this chapter, I share practical tips for making the leap from academia to a career in the technology sector. I argue that there are two primary shifts in mindset required to make the leap and be successful: a shift from ideation to execution and creating value and understanding that the core function of your new job is engineering. I focus on developing skills and tools, crafting a résumé, and preparing for interviews in order to make your transition smoother.

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References

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Resources

SQL

Git

CLI

Python

  • Google’s Python Class https://developers.google.com/edu/python

  • Automate the Boring Stuff with Python: Practical Programming for Total Beginners by Al Sweigart

  • Effective Python: 90 Specific Ways to Write Better Python, 2nd ed. By Brett Slatkin

Machine Learning

  • Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems 3rd ed. by Aurélien Géron

  • An Introduction to Statistical Learning: with Applications in R, 2nd ed. by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani

  • Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd ed. by Trevor Hastie, Robert Tibshirani, and Jerome Friedman

  • Machine Learning: A Probabilistic Perspective by Kevin P. Murphy

Big Data

  • Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems by Martin Kleppmann

  • Learning Spark: Lightning-Fast Data Analytics. 2nd ed. By Jules S. Damji, Brooke Wenig, Tathagata Das, and Denny Lee

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Barnes, M. (2023). So You Want to Work in Tech: How Do You Make the Leap?. In: Jackson, N. (eds) Non-Academic Careers for Quantitative Social Scientists. Texts in Quantitative Political Analysis. Springer, Cham. https://doi.org/10.1007/978-3-031-35036-8_15

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