If you’re applying for a job in the field of data science, data engineering, or business analytics, there’s a good chance that you’ll have to work with SQL at one point or another. Knowing how to manage and query your own data is incredibly important in these fields. If you’re new to SQL, or need to brush off a rusty set of skills to address the current marketplace, it can be difficult to figure out what you need to know about SQL in order to be competitive in your field.

That being said, here are the basics:

Invented in 1974…

The data science career path from junior to senior data scientist varies greatly in skill level, responsibilities, daily tasks, and everyone’s favorite topic- total compensation.

For any kind of technical role, including data science, there are two paths: the management path and the individual contributor path.

The individual contributor path includes data scientists who work on core projects, contribute code, run analyses, and build ETL pipelines and machine learning models. The management path encompasses data scientists who manage people, scale data strategy, and work on fitting the pieces of a data organization together.

Check out our machine learning interview prep…

How many A/B test variants has your email inbox been subjugated to throughout Black Friday? Only a decade or two before, marketers were mostly flying blind on any commercials and posters for sales and promotions.

Now the average e-commerce company probably runs one too many A/B tests on their customers. At Interview Query we tried something similar for our Black Friday promotion by offering 25% off and sending an email about it.

My goal was to run an experiment to learn about how much email copy and content matters. …

Today I’m writing about how I hired a data scientist for my company, Interview Query, by applying data science to the hiring process. My first time hiring a data scientist really opened my eyes to being on the other side of the table after spending years interviewing as a candidate.

There were three main take-aways that I want to dive into.

1. Define the data science role and responsibilities. Know exactly what the data scientist will be working on.
2. Evaluate candidates at scale with automated testing and rubrics, and not endless resume reviewing and hiring manager calls.
3. Creating a metrics based…

Zoom Video Communications, Inc. is an American communications tech company founded in 2011 and headquartered in San Jose, California. The company offers video conferencing and online chat services via a cloud-based software platform that helps transform real-time collaboration experiences. Unlike other competitors, Zoom offers a unified meeting experience with a 3-in-1 platform consisting of HD video conferencing, mobility, and web meetings.

At Zoom, data plays an integral role in understanding and improving user experiences, and the data science team lies at the foundation of the company’s success. …

Introduction

As one of the leading technology companies across the globe, Amazon leverages big data to improve its extensive E-Commerce platform. Data on every customer interaction is gathered and analyzed– from the discovery of a product, to its purchase, and even to its eventual delivery. To refine site performance and improve customer experiences, Amazon feeds this data into its recommendation system, which displays the most relevant products for each customer.

The process of creating a personalized screen of recommendations extends to all of Amazon’s products and services, including Alexa, Prime Video, and Twitch. Business intelligence engineers translate the large data warehouse…

‌‌What Does A Research Scientist Do? ‌‌

The divide between research scientists and data scientists isn’t clearly defined, but generally, research scientists are responsible for building and developing models in a very niche field using complex machine learning, mathematics, and deep learning theory.

While data scientists and adjacent positions work with broad swaths of data and metrics, research scientists encapsulate a deep understanding within a specific area of expertise, working cross-functionally with different teams to develop prototypes and validate hypotheses.

Required Skills and Qualifications for a Research Scientist

The requirements for research scientists largely vary by company: some have more stringent standards, while others are more flexible on the number of years of experience, degree…

Today, we’re talking about data science salaries.

Obviously, this is a huge- and typically taboo- question to ask just anyone, so in the spirit of full transparency, I’ll be telling you how much I’ve made in all of my data science positions ever since I’ve graduated.

First of all, let’s cover some basics.

Your pay will very much depend on the company you’re working for, with respect to their size, how much funding they’re willing to allocate to you, and lots of other factors. …