A row of four R2D2s robot models from the movie Star Wars in a movie theater lobby surrounded by people.
PHOTO: rmkoske

When it comes to emerging job roles, data and artificial intelligence (AI) continue to trend upward, according to the LinkedIn 2020 Emerging Jobs Report. Shocking, right? Whether it’s on the employee- or customer-facing side of the organization, data and AI are in many conversations today in the workplace. 

It therefore makes sense these roles — “AI Specialist” came in at No. 1, 74% annual growth and “Data Scientist” came in at No. 3, 37% annual growth — made the top five in LinkedIn’s third annual report. “Robotics Engineer” came in at No. 2, at 40% annual growth, “Full Stack Engineer” came in No. 4, 35% annual growth and “Site Reliability Engineer” came in No. 5, 34% annual growth. “Many jobs that have risen up as a result of AI in fields like cybersecurity and data science, and because it’s is so pervasive many roles may demand more knowledge of AI than you may think,” said Guy Berger, principal economist at LinkedIn, in a blog about the report. 

Trends With Top 5 Emerging Roles 

We caught up with some practitioners who actually carry some of the titles in LinkedIn’s report. But before that, a bit about each of the top five roles:

  • AI Specialist: Hiring for this role has grown 74% annually in the past four years, according to the LinkedIn report. Some of the skills include: machine learning, deep learning, TensorFlow, Python and natural language processing.
  • Robotics Engineer: LinkedIn officials reported that UiPath, a robotics solutions, was recently valued at $7 billion. Careers in robotics engineering, they found, can vary greatly between software and hardware roles. Increasingly, these roles work on both virtual and physical bots. Skills include Robotic Process Automation (RPA), robotics and using tools like UiPath, Blue Prism and Automation Anywhere.
  • Data Scientist: Data science is a specialty that is growing significantly across all industries, according to LinkedIn. Previous jobs like statistician are evolving, and skills for data scientist includes machine learning, data science, Python, R and Apache Spark.
  • Full Stack Engineer: These practitioners serve as a "valuable asset" to any company, LinkedIn found. Skills unique to the job include React.js, Node.js, JavaScript, AngularJS and Cascading Style Sheets (CSS).
  • Site Reliability Engineer: These folks help ensure your apps are always up and running. They also manage development and operational processes. Skills for this job include Amazon Web Services, Ansible, Kubernetes, Docker Products and Terraform.

Related Article: 7 Jobs That Artificial Intelligence (AI) Will Soon Overtake

Providing Expertise on Robots

Camille Eddy headshot
Camille Eddy

Camille Eddy, robotics engineer and software expert at TIMBER IT Consulting, said her primary responsibilities are checking out the requirements of a robot and sharing that information with stakeholders. She also builds features often repetitive from company to company but new to each client.  “I work on the controls side while others work on the vision side,” she said. “I love my work because I get to create a systematic approach for each company that is unique to them. It's helping an emerging market actually become viable. And I want to see ‘good’ robots become available.”

Intersection of Engineering, Research and Business

Alex Eremia headshot
Alex Eremia
Alex Eremia, founder, CEO and data scientist with BingeWith, said that as a data scientist she works at the intersection of engineering, research and business and can be expected to work with all these teams. “You work to understand how people use your company’s offering,” she said. “You know the ins and outs of the company’s data sources and analyze them to drive the business forward.” 

In data-driven companies, Eremia added, data scientists work directly with engineers, product managers and executives to drive product roadmaps and improvements through presentations and proposals. “Given the wide range of folks you’re interacting with communicating your message clearly is crucial,” said Eremia, a former Google analyst. “With data it’s easy to cause more confusion than clarity. Getting to the punchline and having folks walk out of your presentation repeating the few main points you were trying to make is the best part of the job.”

Related Article: How to Leverage Data Science to Capture the Fickle Consumer

Keeping Amazon Design Principles in Mind

Sara Laprade headshot
Sara Laprade

Sara Laprade, robotics lead design engineer at Amazon Robotics, said she spends time evaluating and creating physical processing and material handling solutions using cutting edge technology, robotics and data analytics to meet product flow requirements based on Amazon design principles. “These are things,” she said, “such as coordinating with systems and operations engineering teams to develop product features and optimize the performance of certain types of Amazon facilities.” She gets to develop models to solve complex problems, all while managing multiple projects and tasks simultaneously and effectively. 

Laprade also influences, negotiates and communicates with internal and external business partners, contractors and vendors. “I always try to identify and analyze key operational and financial metrics in order to drive smart decisions,” Laprade said. 

Inspired by Problem Solving

What makes Laprade passionate about her role at Amazon Robotics? She has always been inspired by problem-solving. “There is something in my brain that ignites when I have an idea for something that is going to have a large impact on the future of package movement and overall warehouse design,” Laprade said. “I’m very much a team person that enjoys working with others who want to transform a customer’s experience before the customer even knows they need the improvement.” 

The robotics engineering field does just that: “It lets those of us who are always hungry for more keep grinding away,” Laprade said. “Because robotics is also such a new space, the runway to opportunities is wide and long. Even though we sometimes have to dive into the weeds for very specific metrics and financial analysis, I have just as much opportunity to pull myself out of the weeds and provide a holistic version and cohesive strategy for next generation designs.”

Related Article: Are Robots Ready for Prime Time?

Solving Hypotheses Brings Passion to Data Science

Archie Jain headshot
Archie Jain

Archie Jain, data scientist at LogMein, shared with CMSWire some of her primary roles and responsibilities:

  • Build predictive models and leverage machine-learning algorithms to apply data science techniques to internal data to address business issues and drive improved outcomes of KPIs, such as retention and expansion of revenue.
  • Partner closely with the head of customer experience, supporting them as they develop strategy and build execution plans.
  • Work with business intelligence analysts to bolster their analyses with intelligent predictions.
  • Conduct analysis of proposed and existing calls-to-action (CTAs), which guide go-to-market teams to intelligently engage with large customer base.
  • Develop hypotheses, in tandem with organizational leaders, for how to test new tactics and approaches; own test design and ensure proper execution and communication of final measurement/conclusions.

“Data Science can help solve multiple use cases with a simple analytical approach,” Jain said. “My job not only involves data collection, cleaning, preprocessing and applying machine learning techniques but also an aptitude and business understanding to capture the underlying problem and how it can be tackled with the right data. As you delve more into data, business questions can be answered and solving these hypothesis with my data science skills makes me passionate about my role.”

Looking Ahead to Eternal Life Because of AI?

Tyler Suard headshot
Tyler Suard

Tyler Suard, an artificial intelligence specialist and a former Python developer who also worked on embedded systems, machine learning and micropython, said his specialty is to first get data from his supervisors or from publicly available resources. Then, he'll modify it to remove any false or useless pieces. "Then, I feed it into an AI and get answers when I come back to it," Suard said. "A lot of my job also has to do with researching the latest methods for how to build better AI."

Suard is "super passionate about AI" because it can do "incredible" things. Future promises are exciting, too, he said. "Some believe that in 20 years, technology will be smarter than biology, and we will no longer die because smart machines can keep us alive forever," Suard said. "Personally, I have always been interested in interstellar space travel, and I think that AI might hold the key to visiting other stars more quickly."