A Reality Check on Data Science
By Lukas Houpt
Article Review
A Brief Snyopsis
Click here here for the article
Author Jason Goodman offers wonderful depth and insight into a career in Data Science from both an applicant and current employee’s perspective. He provides interview skills, strategies for learning code professionally, general (and somewhat subjective) real-world advice on college courses to take, and a narrative of his day-to-day.
This is not what Data Science looks like! Remain calm.
Imposter Syndrome
The vastness of data science tools and expectations often comes off as intimidating.
“Every time I heard someone mention a tool I didn’t know in conversation, I used to silently freak out internally and make a mental note to find a Coursera class on the topic I could binge, stat.”
Fortunately, Goodman simply stresses the ability to master your basic tools and become and expert in a domain.
Relevant Skills Mentioned
Below are the author’s thoughts on relevant skills pertinent to current and aspiring data scientists.
relevant_skills <- list("statistics", "computer science", "philosophy", "history",
"english", "economics", "quantitative psychology", "persuasive speaking", "critical thinking",
"technical skills", "communication", "written", "verbal", "visual")
relevant_skills[[1]]
[1] "statistics"
[[2]]
[1] "computer science"
[[3]]
[1] "philosophy"
[[4]]
[1] "history"
[[5]]
[1] "english"
[[6]]
[1] "economics"
[[7]]
[1] "quantitative psychology"
[[8]]
[1] "persuasive speaking"
[[9]]
[1] "critical thinking"
[[10]]
[1] "technical skills"
[[11]]
[1] "communication"
[[12]]
[1] "written"
[[13]]
[1] "verbal"
[[14]]
[1] "visual"About the Author
Jason Goodman
name is a employment and identifies as fact.
Jason Goodman is a Data Scientist at Airbnb and identifies as “ever curious.”
A Complaint
The buzzwords of Data Science are attractive, and employees have free rein in using and identifying with them. Somehow I wound up taking 3 classes involving data visualization and analysis, and we’ve spent the first TWO WEEKS of each class speculating about and defining Data Science. This is surely a fun and useful exercise, but I signed up to learn the answer to that question, not have it asked of me on day 1. Professors and instructors: take no offense :)