- A Step-by-Step Guide to Transitioning your Career to Data Science – Part 2 - Jun 7, 2019.
How do you identify the technical skills a hiring manager is looking for? How do you build a data science project that draws the attention of a hiring manager?
- A Step-by-Step Guide to Transitioning your Career to Data Science – Part 1 - May 31, 2019.
If you are looking to transition your career to data science, don't immediately start learning Python or R. Instead, leverage the domain expertise you have accumulated over the years. Here's a foolproof guide on how to do that.
- Why Data Professionals Should Negotiate Every Job Offer - May 16, 2019.
Here are six reasons why you shouldn't feel tempted to jump at the chance and take that job offer as it is without first negotiating.
- 5 Things to Review Before Accepting That Data Scientist Job Offer - May 10, 2019.
Before you get too excited and sign the papers for that new data scientist job, and solidify your role as a new hire, make sure you look over these 5 things first.
- Projects to Include in a Data Science Portfolio - Apr 26, 2019.
“Don’t pick just random projects to work on and add it to your resume or portfolio. Solve a problem that relates to the companies that you’re interested in.”
- Make Your Own Job in Data Science: A High-Risk, High-Reward Approach - Apr 12, 2019.
This article discusses an alternative approach to finding data science jobs that’s also worth considering, although it has some inherent risks: make your own.
- Why Data Scientists Need To Work In Groups - Apr 12, 2019.
If you read this article you will see that the job of data scientist is NOT listed. The rest of this article will explore why it is true that data scientists need to work in groups.
- Compilation of Advice for New and Aspiring Data Scientists - Apr 10, 2019.
Check out this compilation of advice for the new and upcoming data scientist, condensing 30+ pieces of advice into 6 minutes.
- KDnuggets™ News 19:n14, Apr 10: Which Data Science/ML methods and algorithms you used? Predict Age and Gender Using Neural Nets - Apr 10, 2019.
Getting started with NLP using the PyTorch framework; Building a Recommender System; Advice for New Data Scientists; All you need to know about text preprocessing for NLP and Machine Learning; Advanced Keras - Constructing Complex Custom Losses and Metrics; Top 8 Data Science Use Cases in Gaming
- How to Recognize a Good Data Scientist Job From a Bad One - Apr 9, 2019.
Here are six characteristics which set good data scientist jobs apart form the bad ones.
- Cracking the Data Scientist Interview - Jan 29, 2019.
After interviewing with over 50 companies for Data Scientist/Machine Learning Engineer, I am going to frame my experiences in the Q&A format and try to debunk any myths that beginners may have in their quest for becoming a Data Scientist.
- Think Twice Before You Accept That Fancy Data Science Job - Dec 19, 2018.
Before you figure out what skills you need to freshen up on, or the most optimal driving path to work to avoid traffic patterns, you need to make sure this new role is a right fit and that you'll be happy working there.
- KDnuggets™ News 18:n48, Dec 19: Why You Shouldn’t be a Data Science Generalist; Industry Data Science & Machine Learning 2019 Predictions - Dec 19, 2018.
Also: Top Stories of 2018; NLP Breakthrough Imagenet Moment has arrived; Four Approaches to Explaining AI and Machine Learning; Solve any Image Classification Problem Quickly and Easily
- Why You Shouldn’t be a Data Science Generalist - Dec 14, 2018.
But it’s hard to avoid becoming a generalist if you don’t know which common problem classes you could specialize in in the fist place. That’s why I put together a list of the five problem classes that are often lumped together under the “data science” heading.
- Data Science Projects Employers Want To See: How To Show A Business Impact - Dec 4, 2018.
The best way to create better data science projects that employers want to see is to provide a business impact. This article highlights the process using customer churn prediction in R as a case-study.