Data Analytics Career Orientation

Considering a Data Analytics career? Today's episode with YouTube icon Luke Barousse (273k subscribers) will be particularly appealing to you, but the terrifically interesting guest makes for an episode that anyone will love.

Luke:
• Is a full-time YouTuber, creating highly educational — but nevertheless hilarious — videos focused on Data Analytics.
• Previously worked as a Lead Data Analyst and Data Engineer at BASF.
• Worked for seven years in the US Navy on nuclear-powered submarines.
• Holds a degree in mechanical engineering, a graduate qualification in nuclear engineering, and an MBA in business analytics.

In this episode, Luke details:
• The must-have skills for entry-level data analyst roles.
• The data analyst skills mistakenly and erroneously pursued by many folks considering the career.
• How his submariner experience prepared him well for a data career.
• His favorite tools for creating interactive data dashboards.
• His favorite scraping libraries for collecting data from the web.
• The skills to learn now to be prepared for the data careers of the future.
• The benefits of CrossFit beyond just the fitness improvements.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Data Analyst, Data Scientist, and Data Engineer Career Paths

Keen to become a Data Analyst? Get promoted to Sr Data Analyst? Or explore Data Engineer/Scientist options? Shashank, a YouTube expert on these questions (>100k subscribers!) tackles them in today's episode.

Shashank:
• Has an exceptional YouTube channel focused on helping people break into a data analyst career.
• Works as a Senior Data Engineer at digital sports platform Fanatics, Inc.
• Was previously Data Analyst at luxury retailer Nordstrom and other firms.
• Holds a degree in chemistry from Emory University in Atlanta.

Today’s episode will appeal primarily to folks who are interested in becoming a data analyst, or who are interested in transitioning from a data analyst role into a data science or data engineering role.

In this episode, Shashank details:
• How you can land an entry-level data analyst role in just a few weeks, regardless of your educational and professional background.
• The hard and soft skills you need to progress from a junior data analyst to a senior data analyst position.
• What it takes to transition from data analyst to a typically more lucrative role as a data scientist or data engineer.
• His favorite resources for learning the essential skills for data scientists.
What he looks for when he’s interviewing candidates.

The SuperDataScience show's available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Geospatial Data and Unconventional Routes into Data Careers

This week, the remarkably well-read Christina Stathopoulos, details open-source software for working with geospatial data... as well as how you can navigate your data-career path, no matter what your background.

Christina:
• Has worked at Google for nearly five years in several data-centric roles.
• For the past year, she’s worked as an Analytical Lead for Waze, the popular crowdsourced navigation app owned by Google.
• Is also an adjunct professor at IE Business School School in Madrid, where she teaches courses on business analytics, machine learning, data visualization, and data ethics.
• Previously worked as a data engineer at media analytics giant Nielsen.
• Holds a Master’s in Business Analytics and Big Data from IE Business School and a Bachelor’s in Science, Tech, and Society from North Carolina State University.

Today’s episode will appeal to a broad audience of technical and non-technical listeners alike.

In this episode, Christina details:
• Geospatial data and open-source packages for working with it.
• Her tips for getting a foothold in a data career if you come from an unconventional background.
• Guidance to help women and other underrepresented groups thrive in tech.
• The hard and soft skills most essential to success in a data role today.
• Her #bookaweekchallenge and her top data book recommendations.

The SuperDataScience show's available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Effective Pandas

Seven-time bestselling author Matt Harrison reveals his top tips and tricks to enable you to get the most out of Pandas, the leading Python data analysis library. Enjoy!

Matt's books, all of which have been Amazon best-sellers, are:
1. Effective Pandas
2. Illustrated Guide to Learning Python 3
3. Intermediate Python
4. Learning the Pandas Library
5. Effective PyCharm
6. Machine Learning Pocket Reference
7. Pandas Cookbook (now in its second edition)

Beyond being a prolific author, Matt:
• Teaches "Exploratory Data Analysis with Python" at Stanford
• Has taught Python at big organizations like Netflix and NASA
• Has worked as a CTO and Senior Software Engineer
• Holds a degree in Computer Science from Stanford University

On top of Matt's tips for effective Pandas programming, we cover:
• How to squeeze more data into Pandas on a given machine.
• His recommended software libraries for working with tabular data once you have too many data to fit on a single machine.
• How having a computer science education and having worked as a software engineer has been helpful in his data science career.

This episode will appeal primarily to practicing data scientists who are keen to learn about Pandas or keen to become an even deeper expert on Pandas by learning from a world-leading educator on the library.

The SuperDataScience show's available on all major podcasting platforms, YouTube, and at SuperDataScience.com.