Top Industries Hiring for Machine Learning, Data Science in 2020
As the Managing Director at Workbridge Associates, I oversee the office and lead a team in Washington D.C. focused on placing data and machine learning professionals within the tech industry. Based on what I’ve been seeing in the market and what I heard from the experts behind this Machine Learning, Data Science Q+A, data-related jobs have spiked in the past few years, and even more since the pandemic began in March.
A number of companies and institutions have stepped up to help fight COVID-19 and solve for challenges that come along with it. Many are quickly applying Machine Learning, Data Science, and Artificial Intelligence to provide solutions, whether through productive analysis, treatments, prediction models, and more. According to Dice’s Tech Jobs report, the need for Data Science and Machine Learning professionals has increased by an average of 50% across several industries in 2020, largely influenced by the effects of the virus. This increased demand has exposed an even greater talent shortage.
Knowing this is such a prominent need in the tech industry, we passed some of our market knowledge on to Tech in Motion, our event series, to host a webinar on the topic. With over 200,000 members nationally, Tech in Motion hosts networking events with the goal of giving back to the tech communities we serve. Since shifting from in-person events to virtual tech talks, Tech in Motion has provided our audience with webinars focused on impactful tech trends in today’s climate.
With so many challenges and opportunities within Machine Learning, Data Science in 2020, Tech in Motion invited the following experts to speak on a panel.
- Elizabeth Owen, Ph.D., Data Science Consultant at Google
- Alexis Roos, Senior Manager of Data Science at Twitter
- Curtis Bennet, Solutions Architect at Vertica
Based on my takeaways from the webinar and observations in the marketplace, these are the leading industries seeking machine learning, data science, and automation engineers.
Healthcare Industry
The most immediate need for Data Science and Machine Learning professionals is within the healthcare industry. This crisis has highlighted the need for transparency and quality of data. People’s lives depend on the availability of data from antibody tests and tests for COVID-19. Machine Learning and Data Science professionals are analyzing data provided by the CDC and other organizations to find a vaccine and treatments to aid Coronavirus recovery. One focus of these studies is to analyze data from existing drugs with the goal of predicting efficacy levels before reaching trials, thus speeding up the roll out to markets.
Additionally, AI is using this same data to expedite the diagnosis process by identifying differences in CT scans between patients infected with COVID-19 and those with ordinary viral pneumonia with 96% accuracy. Additionally, use of AI has reduced the diagnosis time from five minutes to 20 seconds.
Telecommunications Sector
As companies ramp up efforts to keep people connected and sustain the increased internet usage, team collaboration services like Microsoft Teams are encountering bugs and errors resulting in up to 250+ tickets per hour. Virtual sharing dashboards such as Google Docs saw an increase in use of 42%. Every day is a network test for phone companies and internet providers due to the massive amounts of usage that they've never seen before.
More than 44% of the US population faced network degradation due to traffic congestion with download speeds falling by 24%. Companies like Zoom and GoToMeeting are struggling with the demand and usage of their systems, whereas companies like AirBnB are trying to figure out a way to monetize their service. As a result, data science will have a direct impact on a new wave of products that support distance integration and communication which will enable us to connect efficiently and add personalization around the way we use these tools in the future.
E-Commerce & Grocer Companies
With as many as 75% of all restaurants forced to temporarily close due to Government regulations, online shopping activities and food delivery demands have increased by up to 200%. Grocers and e-commerce companies are hiring machine learning engineers to meet the demand of online orders by automating steps in the e-commerce process. For example, Walmart is piloting this process in a mini-warehouse equipped with algorithm-learning robots to move items from warehouse shelves, to carts, to drivers. Some companies are attempting to automate delivery with self-driving vehicles.
Financial Industry
Data and ML professionals are diligently working to analyze and predict data around stocks to rescue hedge fund portfolios. This predictive analysis is also leveraged to speed up lending decisions for small businesses, making funds available only to qualified clients. Data science aids financial institutions by offering a chance to provide better personalization to customers. Financial institutions receive data from several different sources. By using data science, the system gains the ability of data mining, manipulations, and processing. This offers the ability to extract useful insights from the data to improve the efficiency and productivity of the organization.
Fundbox, a San Francisco tech firm, is using this technology to assess the risk with small business borrowers, claiming they can make a lending decision in about three minutes. Speed is of the utmost importance in these unprecedented times, as they estimate many small businesses only have 30 days of operating costs saved. Creating these types of innovations is crucial in helping the U.S. financial markets recover from the COVID-19 pandemic.
Cybersecurity Industry
Cybersecurity attacks have increased by 150% since March 2020 with 61% of employees working from home. Many cybersecurity tool providers have been adding data science capabilities to their cybersecurity platforms. This includes factoring behavior-based analytics into antivirus suites, firewalls, and traffic analyzers to make their products smart. By continually monitoring data entering and leaving the system along with unusual activities, it is possible for data science software and platforms to consistently detect an anomaly as soon as it arrives.
As you can see, the challenges of today’s market are actively impacting companies across a variety of industries, resulting in an increased demand for tech talent to support those needs. Despite an 11.1% unemployment rate in the United States in June 2020, the unemployment rate for individuals in computer-related jobs was reported as 2.5% for the same period.
So what does this mean for you?
- If you’re a hiring manager, fill any gaps in your tech team now, before the talent shortage worsens. Look at alternative options like contracting, if your company isn’t hiring full-time. Invest in the talent you’ll need now that’s already hard to find, like these 5 most in-demand tech roles. Not sure where to start? Contact a local recruiting consultant here
- If you’re a tech job seeker, consider narrowing your search to the resilient industries above that are likely hiring for data science, ML and automation professionals. And sharpen up on the most in-demand skills for 2020 if you can - the value is sure to come back twofold to you.
For more information and to read the full Machine Learning, Data Science Q&A from Tech in Motion’s webinar, visit the website here.
Data Scientist at Siemens
4yWell written Greg Olsen. Enjoyed reading the article.
Data Engineer contractor onsite at Meta
4yVery interesting read, Greg Olsen.