Course Website and Github

2012: Let the wild rumpus begin!

2012-2019: golden age of data science

2012-2019: golden age of data science

• 2013: Universities offer courses in a hot new field data science, April 11 2013, New York Times

• 2017: The data scientist skill table makes it look like a unicorn (data scientist skill set map in our 2017 course)

• 2018: Two aha moments

  • A tale of two machine learning (a cooking analogy)
  • You don’t need to use machine learning to be a data scientist

• 2019: three tracks of data science and de-demonization of deep learning (What’s coming in TensorFlow 2.0, Jan 2019)

Is data scientist still sexy?

Is data scientist still sexy?

• 2020 - 2021: pandemic, layoff and hiring freeze, hiring spree

Is data scientist still sexy?

In demand but not sexy

What has changed?

You tell someone: "I am a data scientist."

What has changed?

• More DS education programs

• Title creation and shift: Analyst → scientist, scientist → research

• Title inconsistency across different companies/industries

• Better job definition (within an organization)

• Standard interviewing process

Titles in/related to data science

• Data infrastructure engineer
• Data engineer
• Business intelligence (BI) engineer
• Analytics engineer
• Machine learning engineer
• Data scientist
• Economist
• Applied scientist
• Data analyst
• Product analyst
• Quant researcher: UX, market, finance
• Research scientist
• Quant analyst
• Business analyst

Identity crisis is real!

Three tracks of data science

Three tracks of data science

Three tracks of data science

Technical key words (danger zone!)

This is example only. It does NOT represent the tiles v.s. skills in all companies.

• Data infrastructure engineer: Go,Python, AWS/Google Cloud/Azure, logstash, Kafka, and Hadoop
• Data engineer: spark/scala, python, SQL, AWS/Google Cloud/Azure, Data modeling
• BI engineer: Tableau/looker/Mode etc, data visualization, SQL, Python
• Data analyst: SQL, basic statistics, data visualization
• Data scientist: R/Python, SQL, basic + applied statistics, data visualization, experimental design
• Research scientist: R/Python, advanced statistics + experimental design, ML, research background, publications, conference contributions, algorithms
• Applied scientist: Similar to research scientist, ML algorithm design, often with an expectation of basic software engineering skills
• Machine Learning Engineer: More advanced software engineering skill set, algorithms, machine learning algorithm design, system design
• ...

Data Science Roles

This is example only. It does NOT represent the tiles v.s. skills in all companies.

Data Science Types v.s Needs

DS across companies

IC v.s. People Manager

Startup v.s. Mature company (Pre IPO/Public)

Reference

• Short courses in the past: 2017, 2018, 2019, 2020, 2021

• (Kaggle) State of Data Science and Machine Learning: 2017, 2018, 2019, 2020, 2021

Websites:

• Data Scientist: The Sexiest Job of the 21st Century, Oct 2012, Harvard Business Review

• Universities offer courses in a hot new field data science, April 11 2013, New York Times

• Tech role compensation

• Mode SQL tutorial(those are not video but text. I find it very helpful. But if you use SQL daily, the best helper is still Google search…)