Principal Data Scientist Resume Example & Writing Guide
Use this Principal Data Scientist resume example and guide to improve your career and write a powerful resume that will separate you from the competition.
Principal data scientists are the top data scientists in an organization—the ones who set the direction for their team and define the future of their company. Their expertise is critical in helping organizations make sense of the massive amounts of data they’re generating every day.
Principals are often in charge of building out teams of data scientists, defining the roles and responsibilities of their new hires, and setting guidelines for how they should work. They also play a key role in communicating their findings to the rest of the company—whether it’s through presentations, reports, or just conversations with colleagues.
If you’re looking to take your data science career to the next level—or just looking for a new challenge—here are some tips and an example resume to help you write a compelling principal data scientist resume that hiring managers will love.
How to Write a Principal Data Scientist Resume
Here’s how to write a resume of your own.
Write Compelling Bullet Points
The best bullet points are those that are specific and highlight your most important skills and accomplishments. So rather than saying you “developed new algorithms,” you could say you “developed new machine learning algorithms to increase customer conversion rate by 15%.”
The second bullet point is much stronger because it provides specific details about what you did and the outcome of your work.
Identify and Include Relevant Keywords
When you apply for a job as a data scientist, your resume is likely to go through an applicant tracking system (ATS). This system will scan your resume for certain keywords related to the job opening. If your resume doesn’t have enough of the right keywords, the ATS might automatically reject your application.
The best way to make sure you have the right keywords on your resume is to take a look at the job posting and use those same words throughout your resume. Here are some of the most commonly used principal data scientist keywords:
- Machine Learning
- Deep Learning
- Python (Programming Language)
- Artificial Intelligence (AI)
- Data Science
- Natural Language Processing (NLP)
- R (Programming Language)
- Analytics
- Statistical Modeling
- Hadoop
- Algorithms
- Data Mining
- Statistics
- TensorFlow
- Apache Spark
- Predictive Analytics
- SQL
- Pivot Tables
- Linux
- Hive
- Python Data Analysis Library (PDA)
- RStudio
- Apache Kafka
- Statistical Programming
- Apache Hadoop
- Spark SQL
- Tableau
- Machine Learning Algorithms
- Deep Learning Libraries
- Recommendation Systems
Showcase Your Technical Skills
As a data scientist, you know that data doesn’t speak for itself. It needs to be analyzed, interpreted, and presented in a way that is easy for others to understand. And that’s where your technical skills come in. Recruiters are looking for data scientists who are proficient in programs like R, SAS, MATLAB, SPSS, and Stata, and who have experience with data mining, machine learning, and modeling. They also want to see that you have a solid understanding of big data concepts and platforms like Hadoop, Hive, and Spark.
So if you have experience with any of these programs or platforms, be sure to list them on your resume. And if you’re not familiar with them, now is the time to learn them!
