Prolific data science content creator 🎯 Mark Freeman details what Data Engineering is and why it's a critically useful subject area for data scientists to be proficient in. Hear all about it in this week's episode.
Mark:
• Is a Senior Data Scientist, with a Data Engineering specialization, at Humu (startup that has raised $100m in venture capital).
• Posts data science and software engineering tips daily on LinkedIn.
• Previously was data scientist at Verana Health and data analyst at the Stanford University School of Medicine.
• Also holds a Master’s in Community Health and Prevention Research from the Stanford medical school.
Today’s episode is geared toward listeners who are already in a technical role such as data scientists, data engineers, ML engineers, or software engineers — as well as to folks who’d like to grow into these kinds of roles.
In today’s episode, Mark details:
• The differences between junior, senior, and staff data scientists.
• What it takes to get promoted into more senior data science roles.
• How data engineering differs from data science.
• His top tools for data extraction, modeling, and pipeline engineering.
• His top tip for getting hired at a fast-growing VC-backed startup.
• How behavioral nudges can drastically improve workplace experiences.
• Why all data scientists should be interested in web3.
The SuperDataScience show's available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
