It's 2023 and we are settling into a post-pandemic hybrid working world--the fact remains that video interviews are here to stay.
For hiring managers, video calls offer a way to screen candidates before scheduling face-to-face or in-person time with senior staffers. This means that no matter what industry or role you apply for, chances are you will have to complete a video interview, or even a series of them.
However, just because we've spent almost three years communicating digitally doesn't mean that everyone has nailed it--here are seven ways to make a great impression with a video interview.
1. Pick your background
This might sound obvious, but you'd be surprised how many people don't consider the background at all during video calls. Your kitchen, bedroom or family room might be fine for a casual catch up with long-standing colleagues or friends, but do you really want a prospective employer seeing what you're planning for dinner, that heap of ironing, or family snaps from a recent vacation?
The point of a plain background isn't to hide your real self, but rather to avoid distracting the interviewer. You want them to focus on what you have to say, not trying to read book titles from the shelves behind you.
2. Use your phone
It may seem a little less professional to use your phone over a laptop to join the video call, but the camera on your phone is generally going to be considerably better than the one on your laptop.
Just make sure to place your phone on its side so the picture is landscape not portrait as this will look better on a screen, for those on the other end of the call. Always do a trial on your phone prior to the meeting, especially if you need to download an app to access all functionalities, such as the ability to blur backgrounds.
3. Use an external microphone
We can all forgive questionable camera work, but poor quality sound is much harder to work through.
External microphones aren't expensive and will increase the perception of your professionalism considerably. It goes without saying that you should buy a microphone that not only works with your phone, but also provides an earbud option if you cannot control background noise.
4. Opt for eye contact
Despite being almost a number of years into remote working, the majority of people still look directly at the people on their screen, or at themselves, instead of into the camera.
You will create a much more personable impression if you speak and look at the camera, not the hiring manager. If you struggle with this, position your phone so that the camera is at eye level.
5. Practice
Not talking over the interviewer or trying not to interrupt them is so much harder when you're not in the same room so practice your technique with a friend and adopt the three second rule. Before you speak, wait three seconds to make sure everybody else in the meeting is finished--this is especially important if you have a tendency to ramble when you're nervous.
6. Be comfortable
It's often the most obvious points that trip people up, so remember comfort is key. Your call could go on for an hour, can you comfortably sit in the same position that long?
The background and light in your bedroom might be the best in the house, but can you sit on the edge of your bed for 60 minutes? It's worth sacrificing the perfect set up for comfort and a lack of distraction.
7. Accept interruptions
You should of course try to minimize interruptions from kids, pets or family members, but life happens. So if there is an interruption or a tech issue, accept it, address it, and move on.
Post-covid we are all much more adept at video meetings, and so understand that mistakes happen. How you deal with it shows more about you than you might think. It reveals to your interviewer how you deal with problems or setbacks, so remain calm and professional, and move on.
The Tech Times Job Board is full of companies with opportunities for professionals across all sectors and levels. Now that you know how to ace that video interview, why not put it to the test? Below, you'll find three exciting roles to check out.
Staff Scientist, Shopify
As Staff Scientist across merchant services with Shopify you will focus on pushing products and the business forward, with a focus on solving important problems rather than specific tools. You will be responsible for proactively identifying and championing projects that solve critical problems for merchants while working closely with product, engineering and other business leaders to influence product and program decisions with data. You will have at least seven to 10 years' of commercial experience as a data scientist, and extensive experience launching productionized machine learning models at scale. Apply for the Staff Scientist role or browse all available opportunities at Shopify.
AI Specialist, Meta
As an AI Specialist with Meta you will work with the AI Compiler team to develop a comprehensive AI Compiler strategy that delivers a highly flexible platform to explore new DL/ML model architectures. You will be responsible for the development of the industry-leading PyTorch ML framework core compilers to support new state of the art inference and training ML HW accelerators, and optimize their performance while analyzing deep learning networks to develop and implement compiler optimization algorithms. You will need effective experience with C/C++ programming skills and experience in accelerating deep learning models or libraries on hardware architectures. Get all the details on the AI Specialist role or discover other opportunities at Meta.
Data Scientist Lead, Trust and Safety, OpenSea, Remote
OpenSea is the first and largest marketplace for non-fungible tokens, or NFTs. It is hiring a Data Scientist Lead, Trust and Safety to build the foundational data solutions for OpenSea's trust and safety challenges. You will apply your data skills to protect the NFT ecosystem and collaborate closely with engineering, product, policy and operations teams and conduct thorough data insights. You'll create, standardize, and improve metrics reporting, and launch experimentation too. To apply, you will need a Bachelor's degree in computer science or a related technical field, four plus years' of experience in data science, analysis, machine learning or equivalent roles. Apply for the Data Scientist Lead, Trust and Safety job or check out all opportunities at OpenSea.
