As a new technical recruiter, it is easy to get lost in all the technical lingo. Java and JavaScript are similar but entirely different when it comes to what they are used for and someone skilled in Java is not appropriate for JavaScript roles and vice versa. Worse is when the same exact same skill can be used in a variety of contexts 🤦🏻 Yes, software engineers like to make it harder for the rest of us 😂
One such example which we will cover today is Python.
Python can be used for web development on the backend but it can also be used for data analysis. How can you tell if a candidate is using Python for backend web development or using Python for data analysis?
What phrases, work experiences, educational experiences or skills on a candidate's resume or background would help distinguish the two situations?
First, it's important to understand the differences between these two types of roles. Backend web development involves the design and implementation of the server-side logic and infrastructure that powers a web application. This typically involves working with languages and frameworks such as Python, Ruby, and Django, and may include tasks such as database design, server configuration, and API development. See our guide to backend development for more information.
On the other hand, data analysis involves the use of Python and other tools to extract insights and trends from large datasets. This may involve tasks such as data cleaning, data visualization, and statistical analysis, and may require skills such as machine learning and statistical modeling.
With these differences in mind, here is what to look for in a candidate's resume to determine if they are using Python for backend web development or data analysis:
- Description of what they do: Look for specific phrases and words on the candidate's resume that indicate their focus on either backend web development or data analysis. For example, phrases such as "server-side development" or "web application development" or "fullstack development" may indicate a focus on backend web development, while phrases such as "data modeling" or "data cleaning" or "statistical analysis" may indicate a focus on data analysis.
- Titles: The candidate's title can also provide clues about their focus on backend web development or data analysis. Some titles such as "Software Engineer" or even "Backend Engineer" can be ambiguous. Others such as "Web Developer", "Application Developer" or "Fullstack developer" indicate using Python for web development. On the other hand, titles such as "Data Engineer" or "Machine Learning engineer" or previous titles such as "Data Analyst" indicate data analysis.
- Skills: Look for specific skills on the candidate's resume that are relevant to backend web development or data analysis. For example, skills such as Django or Flask may indicate a focus on backend web development. Similarly frontend skills such as React.js or Angular.js also likely indicate web development as a data analysis focused engineer wouldn't know them. On the other hand, skills such as machine learning, statistics, Pandas, R, or data visualization likely indicate a focus on data analysis.
- Educational experiences: The candidate's educational experiences can also provide insights into their focus on backend web development or data analysis. A coding bootcamp probably indicates web development whereas previous background in statistics or mathematics will likely hint at the opposite.
To summarize, by looking deeper at work experiences, educational experiences, and skills on the candidate's resume that mentions Python, you can get a better understanding of their focus on backend web development or data analysis, and determine if they are a good fit for the role you are trying to fill.
More importantly, you can avoid sending the wrong type of candidate to a hiring manager and losing their confidence in you!
About Rocket
Rocket pairs talented recruiters with advanced AI to help companies hit their hiring goals. Rocket is headquartered in the heart of Silicon Valley but has recruiters all over the US & Canada serving the needs of our growing client base across engineering, product management, data science and more.
