- Glassdoor shows 3,937 companies in the middle of a hiring surge during Covid-19, 960 of which are in information technology.
- Leading software companies going through a hiring surge right now include Aha! Software, Appen, Clevertech, CrowdStrike, Datadog, Dataiku, Fastly, Hashicorp, Leidos, Liveops, Netskope, Proofpoint, Rackspace, Zapier and Zendesk.
- Modern Tribe, Dataiku, Zapier, PartnerCentric, Slack, Fuse, ScienceLogic and SAP are the highest rated companies by their employees on Glassdoor who offer remote jobs today.
- Between Glassdoor, Indeed, LinkedIn and Monster, there are over 16,500 open remote-based software technical professional jobs available today. Companies with open, remote-based solutions include Aha!, Box, Cloudera, DemandBase, Jobot, Red Hat, NTT Data, Salesforce and many others.
- Freshworks currently has 161 openings, the majority of which are remote. Check out their open positions here on Glassdoor.
- GitLab alone has 79 remote full-time positions open today and is widely considered a leader in creating a productive, positive remote working culture, with 88% of employees saying they would recommend the company to a friend.
These and many other useful insights are based on comparing the leading tech companies who offer remote, work-from-home job positions by their Glassdoor scores. Leading tech companies are ranked on the percentage of employees who would recommend their company to a friend and the percent of employees who approve of the CEO. The total number of open job positions by company is in the third column of the table. Hiring companies of note include the following:
PowerToFly has had an impressive growth year and is the go-to remote job search engine for women professionals. The company was launched in 2014 by Milena Berry and Katharine Zaleski to connect Fortune 500 companies, startups and growing companies with women looking to work for businesses that value gender diversity and inclusion. PowerToFly’s number of available remote jobs has soared from 994 earlier this year to over 2,500 open remote positions today. 94% of employees would recommend working at PowerToFly to a friend and 93% approve of their CEOs.
The best tech companies for remote jobs in 2021 table is shown below. You can download the original Excel data set here. Please click on the image to expand it for easier reading.
- Angelist has 2,700 enterprise software-related remote positions on their website today with companies including Auth0, Arctic Wolf Networks, Confluent, Couchbase, HackerOne, Slack, MindTickle, MongoDB, Sendoso, Tanium and many others.
- FlexJobs has 5,566 remote-based software jobs that include full-time, part-time and freelance positions. Open positions include Senior Software Engineers, DevOps Engineers, Product Managers, Project Managers, Full Stack Developers and more.
- Remotive provides a curated list of 192 startups, many of which have open remote-based positions on December 1, 2020.
- StackOverflow has 815 open remote-based job positions available today, including Canonical (39 open jobs), Octane AI, Shield AI and many others.
- Torch Capital’s Talent Connect Portal has 980 positions open today, including several from DoubleVerify, Electric, Lexis Nexis, Nexon America, Shopify, Tesla and others.
- Working Nomads site currently has 11,216 remote, work-from-home development jobs advertised. There are also 2,021 marketing, 1,922 management, 1,873 system administration, 1,592 design and 1,164 sales remote, work-from-home job postings.
The most common request from this blogs’ readers is how to further their careers in analytics, cloud computing, data science, and machine learning. I’ve invited Alyssa Columbus, a Data Scientist at Pacific Life, to share her insights and lessons learned on breaking into the field of data science and launching a career there. The following guest post is authored by her.
Earning a job in data science, especially your first job in data science, isn’t easy, especially given the surplus of analytics job-seekers to analytics jobs.
Many people are looking to break into data science, from undergraduates to career changers, have asked me how I’ve attained my current data science position at Pacific Life. I’ve referred them to many different resources, including discussions I’ve had on the Dataquest.io blog and the Scatter Podcast. In the interest of providing job seekers with a comprehensive view of what I’ve learned that works, I’ve put together the five most valuable lessons learned. I’ve written this article to make your data science job hunt easier and as efficient as possible.
- Continuously build your statistical literacy and programming skills. Currently, there are 24,697 open Data Scientist positions on LinkedIn in the United States alone. Using data mining techniques to analyze all open positions in the U.S., the following list of the top 10 data science skills was created today. As of April 14, the top 3 most common skills requested in LinkedIn data scientist job postings are Python, R, and SQL, closely followed by Jupyter Notebooks, Unix Shell/Awk, AWS, and Tensorflow. The following graphic provides a prioritized list of the most in-demand data science skills mentioned in LinkedIn job postings today. Please click on the graphic to expand for easier viewing.
Hands-on training is the best way to develop and continually improve statistical and programming skills, especially with the languages and technologies LinkedIn’s job postings prioritize. Getting your hands dirty with a dataset is often much better than reading through abstract concepts and not applying what you’ve learned to real problems. Your applied experience is just as important as your academic experience, and taking statistics, and computer science classes help to translate theoretical concepts into practical results. The toughest thing to learn (and also to teach) about statistical analysis is the intuition for what the big questions to ask of your dataset are. Statistical literacy, or “how” to find the answers to your questions, come with education and practice. Strengthening your intellectual curiosity or insight into asking the right questions comes through experience.
- Continually be creating your own, unique portfolio of analytics and machine learning projects. Having a good portfolio is essential to be hired as a data scientist, especially if you don’t come from a quantitative background or have experience in data science before. Think of your portfolio as proof to potential employers that you are capable of excelling in the role of a data scientist with both the passion and skills to do the job. When building your data science portfolio, select and complete projects that qualify you for the data science jobs, you’re the most interested in. Use your portfolio to promote your strengths and innate abilities by sharing projects you’ve completed on your own. Some skills I’d recommend you highlight in your portfolio include:
- Your programming language of choice (e.g., Python, R, Julia, etc.).
- The ability to interact with databases (e.g., your ability to use SQL).
- Visualization of data (static or interactive).
- Storytelling with data. This is a critical skill. In essence, can someone with no background in whatever area your project is in look at your project and gain some new understandings from it?
- Deployment of an application or API. This can be done with small sample projects (e.g., a REST API for an ML model you trained or a nice Tableau or R Shiny dashboard).
Julia Silge and Amber Thomas both have excellent examples of portfolios that you can be inspired by. Julia’s portfolio is shown below.
- Get (or git!) yourself a website. If you want to stand out, along with a portfolio, create and continually build a strong online presence in the form of a website. Be sure to create and continually add to your GitHub and Kaggle profiles to showcase your passion and proficiency in data science. Making your website with GitHub Pages creates a profile for you at the same time, and best of all it’s free to do. A strong online presence will not only help you in applying for jobs, but organizations may also reach out to you with freelance projects, interviews, and other opportunities.
- Be confident in your skills and apply for any job you’re interested in, starting with opportunities available in your network. If you don’t meet all of a job’s requirements, apply anyway. You don’t have to know every skill (e.g., programming languages) on a job description, especially if there are more than ten listed. If you’re a great fit for the main requirements of the job’s description, you need to apply. A good general rule is that if you have at least half of the skills requested on a job posting, go for it. When you’re hunting for jobs, it may be tempting to look for work on company websites or tech-specific job boards. I’ve found, as have many others, that these are among the least helpful ways to find work. Instead, contact recruiters specializing in data science and build up your network to break into the field. I recommend looking for a data science job via the following sources, with the most time devoted to recruiters and your network:
- Friends, family, and colleagues
- Career fairs and recruiting events
- General job boards
- Company websites
- Tech job boards.
Alyssa Columbus is a Data Scientist at Pacific Life and member of the Spring 2018 class of NASA Datanauts. Previously, she was a computational statistics and machine learning researcher at the UC Irvine Department of Epidemiology and has built robust predictive models and applications for a diverse set of industries spanning retail to biologics. Alyssa holds a degree in Applied and Computational Mathematics from the University of California, Irvine and is a member of Phi Beta Kappa. She is a strong proponent of reproducible methods, open source technologies, and diversity in analytics and is the founder of R-Ladies Irvine. You can reach her at her website: alyssacolumbus.com.
- Data scientist roles have grown over 650% since 2012, but currently, 35,000 people in the US have data science skills, while hundreds of companies are hiring for those roles.
- Job growth in the next decade is expected to outstrip growth during the previous decade, creating 11.5M jobs by 2026, according to the U.S. Bureau of Labor Statistics.
These and many other insights are from the recently released LinkedIn 2017 U.S. Emerging Jobs Report. LinkedIn has provided an overview of the methodology in their post, The Fastest-Growing Jobs in the U.S. Based on LinkedIn Data. “Emerging jobs” refers to the job titles that saw the largest growth in frequency over that five year period. LinkedIn reports that based on their analysis, the job market in the U.S. is brimming right now with fresh and exciting opportunities for professionals in a range of emerging roles.
Key takeaways from the study include the following:
- There are 9.8 times more Machine Learning Engineers working today than five years ago based on LinkedIn’s research, with 1,829 open positions listed on the site today. There are 6.5 times more Data Scientists than five years ago, and 5.5 times more Big Data Developers. The following graphic illustrates the rapid growth of key data scient, machine leanring, big data and full stack developers in addition to sales development and customer success managers.
- Software engineering is a common starting point for professionals who are in the top five fasting growing jobs today. The career path to Machine Learning Engineer and Big Data Developer begins with a solid software engineering background. The top five highest growth job typical career paths are shown below:
- The skills most strongly represented across the 20 fastest growing jobs include management, sales, communication, and marketing. Additional skills represented across the highest growing jobs include marketing expertise (analytics and marketing automation), start-ups, Python, software development, analytics, cloud computing and knowledge of retail systems.
- LinkedIn interviewed 1,200 hiring managers to determine which soft skills are most in-demand and adaptability came out on top. Additional soft skills include culture fit, collaboration, leadership, growth potential, and prioritization.
LinkedIn Blog: The Fastest-Growing Jobs in the U.S. Based on LinkedIn Data
LinkedIn’s 2017 U.S. Emerging Jobs Report