Boolean-ify Your Data Science Job Search
By: Matt Burke
Tags: Boolean Search, Job Search, Career Change, Data Science, Job Search Tips

Boolean-ify Your Data Science Job Search

The post was originally published 8-April 2020.

Overview

Intended audience: data scientists who are in the job market

Basic introduction to using boolean operators as a targeted strategy to finding data science jobs

Walkthrough of how to refine your job search terms on LinkedIn with a real-life example I’ve used

After reading this article you will:

Understand of how you can use boolean operators to make your job search more fruitful

Have a basic, actionable approach to searching for jobs on LinkedIn

Two important notes:

This article assumes you are familiar with boolean operator search. See here if you’re not or you need a refresher.

Boolean definitions in this post are from BuiltIn.com.

The job search…

Searching for a new job is no walk in the park. The experience is often characterized by feelings that run the gamut of human emotion: excitement, fear, empowerment, fatigue, anticipation, disappointment, confidence, overwhelm. In this post, I introduce a basic yet powerful tool for one approaching a specific aspect of the job search: searching for jobs online. I hope to provide you with actionable information that you can readily apply and, by doing so, hope you feel more empowered and confident in searching for your next job.

Instead of talking in general terms, I’ll illustrate the process by walking you through an example from my life using LinkedIn Job Search. LinkedIn’s job search functionality is a great because:

It includes millions of jobs, with thousands of new jobs posted every day

It’s widely used by recruiters

You can save your search terms and alerted when similar jobs are posted

You can get super specific with your boolean searches

Each section of the walkthrough builds off the prior section. I start with basic boolean searches then build upon the results of those searches to further refine my search. The basic format for each section is as follows:

OPERATOR

What it does : description of operator functionality

: description of operator functionality What I searched: the search term I used on LinkedIn

the search term I used on LinkedIn Example titles returned: the search results

Let’s get started…

AND

What it does: Includes multiple criteria in search results

Includes multiple criteria in search results What I searched: data AND python

data AND python Example titles returned: Data Scientist; Data Analyst; Data Engineer

This first search is intentionally super general. I just want to get an idea of what types of data jobs are out there that require python. It’s also helpful to see what companies are posting data jobs, which will come in useful as I make my searches more specific.

Since I’m not interested in data engineer roles, I’m going to specify that I’m only interested in data scientist or data analyst roles using the OR operator in my next search.

OR

What it does: Includes one or more criteria in search results

Includes one or more criteria in search results What I searched: data scientist OR data analyst AND python

data scientist OR data analyst AND python Example titles returned: Data Scientist; Senior Data Analyst, Agriculture & Commodities; Data Analyst I

The OR operator allows me to search for either data scientist or data analyst roles only. The titles are getting more refined, however, there are two things about these search results that I’m not interested in.

First, I don’t want to work in agriculture. Second, I’m not looking for a Data Analyst I role, as this is too junior for me. The NOT operator will help to refine this.

NOT (-)

What it does: Excludes unwanted criteria from search results

Excludes unwanted criteria from search results What I searched: data scientist OR data analyst AND python -agriculture -I

data scientist OR data analyst AND python -agriculture -I Example titles returned: Senior Data Scientist; Marketplace Operations Senior Business Analyst; Sr. Digital Data Analyst

Great! My search is getting to be even more focused and the results are more in line with what I’m looking for. A few things stand out with these search results that I’ll build upon with my next search.

First, I don’t meet the qualifications for a senior data scientist. Second, I hadn’t considered specifying the type of analyst title. My background is in operations so I’m going to see what kind of results I get when I search for data scientist/analyst jobs with an operations focus. Finally, after looking at various data analyst job descriptions, senior data analyst roles seem to be a good fit for me so I’m going to specify that.

Brackets ()

What it does: Group search phrases and prioritize operators

Group search phrases and prioritize operators What I searched: (sr. OR senior data analyst) OR (data scientist -lead) AND operations AND python -agriculture

(sr. OR senior data analyst) OR (data scientist -lead) AND operations AND python -agriculture Example titles returned: Senior Data Analyst, Sales Compensation; Associate Data Analyst; Senior Global Data Analyst, People Operations

Notice in this search I prioritized senior data analyst roles over data scientist roles. Though I did get a few data scientist results, the vast majority were senior data analyst roles. And this time those roles were more specialized than the generic data analyst roles I was getting from past searches.

I’ll build off these results for my final search. Associate data analyst looks a bit too junior for me, so I’ll exclude that from my next search. For the sake of a highly targeted search, I’m only going to look for specialized senior data analyst roles. Sales compensation sounds boring but sales operations might be interesting. I hadn’t thought about people operations before and that sounds interesting so I’m definitely going to include that.

Quotes “ ”

What it does: Search for exact phrase

Search for exact phrase What I searched: (sr. OR senior data analyst) AND ((sales operations -compensation) OR “people operations”) AND python -agriculture

(sr. OR senior data analyst) AND ((sales operations -compensation) OR “people operations”) AND python -agriculture Example titles returned: Lead Analyst, Solutions Consulting Data and Analytics; Business Data Analyst; Senior Global Data Analyst, People Operations; Sales Operations Analyst

Wow! These results are super specific and all roles that I’m interested in. I hadn’t thought about including “lead” in my search…turns out it’s synonymous with a senior level. The idea of solutions consulting and data analytics sounds interesting too. I’ll be sure to include that moving forward. Upon looking the sales operations role, I don’t think that’s something I’m all that interested in so I’ll probably exclude that.

Wrap up

I hope I’ve proved to you the power of using boolean operators in your job search. And this only begins to scratch the surface! The operators I discussed are only the basics. More advanced operators allow you to refine by things like synonyms, root words, specific sites, and more. If this is interesting to you check out this BuiltIn.com article are take your job search to the next level.