Information Technology (IT) is a wide field, encompassing a ton of jobs and functions. What they have in common is that they’re all aimed at helping organizations improve decision making, allocate and utilize resources better, and operate more efficiently.
In the past, IT typically centered around hardware. But today, IT is broadening its focus to incorporate storing, structuring, transferring, analyzing, and calculating an organization’s data.
Let’s explore some common professions within IT.
IT Job Titles and Descriptions
All of the following jobs fall under the IT umbrella. However, there’s some debate in the community about which really belong. I got many of these from TechRepublic’s Top 10 IT jobs with the hottest outlook for 2017. Others came from related searches.
“When you get to individual companies’ ‘IT’ departments, some separate out stuff like developers and database guys, for example, from network guys and hardware guys,” Sr Software Support Specialist Devin Armstrong told me. “Usually because the network and hardware roles mostly deal with support and maintenance and sometimes building infrastructure. This may be getting complicated since there are gray areas.”
Data scientist/Data engineer/Analytics manager/Database administrator
Data is growing, and with it the need to decide:
- What data to keep and what to discard
- How to store the data you keep
- How to give it the right metadata
“The data tsunami requires us to make decisions about what data to keep and what to discard, and how to store what we keep reliably with the right metadata,” according to a white paper prepared for the Computing Community Consortium committee of the Computing Research Association. Most of this data is unstructured. “For example, tweets and blogs are weakly structured pieces of text, while images and video are structured for storage and display, but not for semantic content and search.”
Unstructured, unlabeled data with no provenance is difficult to analyze and makes analysis more prone to error. “You need to know where your data came from,” the researchers write. “Errors can crop up at any step in your process which compromise the resulting analysis.”
Currently, many organizations store and structure data in an ad-hoc fashion. “Transforming such content into a structured format for later analysis is a major challenge.”
Cynthia Bell, a Sales Operation Manager who studies data science notes that, while there’s a ton of hype around artificial intelligence, “Most companies do not need machine learning. They need someone to create a decent data pipeline that is clean and then also someone who can do basic stats. Like, you can’t have ML and AI and all this nonsense until you have the foundation set and a lot of companies most certainly do NOT have the foundation set.”
This echoed what early stage investment company Bloomberg Beta partner James Cham said in a recent podcast.
I asked my Data Scientist friend Raj Bandyopadhyay for his take. “Most of the time,” Bandyopadhyay said, “companies don’t need very advanced methods in data science, even though they might think they do.”
Here’s what data science actually involves, according to Raj:
1) Infrastructure: Make sure the data is centralized, available and clean. The data should also be documented i.e. people should know what the data means and where to find the data they need.
2) Culture: All the infrastructure in the world is useless if there’s not a culture of using it well. This also includes training people to think more analytically as needed.
3) Analytics methods: There’s a progression of how analytics usually gets incorporated into an organization:
a) Basic analytics and metrics: Most times, companies can get a lot of mileage just by creating some well-thought out charts and dashboards. Visualizing the right data in the right ways can often unlock useful insights
b) Basic statistical analysis: Basic correlations, statistical testing, and descriptive statistics form the next level of analysis. These are not predictive techniques, but they can still be prescriptive.
c) The actual predictive analysis comes after that. This is where you start using machine learning and such techniques. Again, most predictive analysis uses really simple techniques applied well, rather than complex AI stuff.
d) Optimization: this is a phase that most companies don’t get to. It’s about not only using data to predict the future but also using data/algorithms to figure out what to do about it.
My favorite writing on this topic is by Carl Anderson, who wrote a book called Creating a Data Driven Organization. He has a series of blog posts that’s a high-level summary of the book. Here’s the last post in that series.
IT technician/Help desk technician
A good way to start your IT career, this is probably the job you think of when you think “IT.” These are the people you call when you need technical support or help troubleshooting your computer.
According to ITCareerFinder, help desk technicians come in two basic flavors: In-house and remote. You call in-house help desk people when you have a problem with your work computer or internet. Remote techs are the people you call when you have an issue with a product or service.
In this role you’ll likely use help desk software.
A network administrator is responsible for making sure an organization’s computer network is running and up-to-date. Coordination is the name of the game here, as different computers, peripherals, software systems, operating systems, and more need to work together harmoniously.
According to Wikipedia, software engineers design, develop, maintain, test, and evaluate software and systems. Other job titles, which mean essentially the same thing (Don’t @ me), include computer programmer and software developer. It’s a good idea for software engineers to learn Python or R to prepare to supervise machine learning algorithms.
“Software engineering is considered an IT job in the broader job sense,” Devin Armstrong told me. “Now when you get specific you wouldn’t really call a person who only develops software part of the ’IT’ department at a company. I never directly touch or support hardware. A systems engineer may never directly touch actual hardware and just deal with software but that is still under the corporate “IT” definition.”
Here’s a good guide for getting started in the field.
Okay, first things first. I know these are not the same job. But they’re related so I’m lumping them together.
UX stands for “user experience” and just means the experience the user has with the product or brand. The job of the UX designer is to use market research, psychology, testing, and analytics to make sure the user has a pleasant experience. Whether the UX designer has decision-making rights on the product alone or the product and brand, including sales, customer support, and marketing, depends on the company. CareerFoundry described the role as “part marketer, part designer, part project manager.”
UI stands for “user interface,” as in a product or service’s buttons and knobs and links. The UI designer’s job is to use psychology, testing, and analytics to make sure the aesthetic is pleasing to the user and simple to learn and operate.
Quality assurance technician
While quality assurance evolved in the manufacturing context, in IT it mainly means bug testing software and completing processes on websites to make sure they work. For software QA specifically, you may be making sure it meets standards such as ISO 9000 or CMMI. Or you might use enterprise quality management software in this job for tasks including supply chain disaggregation and regulatory compliance.
Security analysts protect their organization’s sensitive data from unauthorized access. They recommend changes to ensure network security and are often responsible for keeping hardware and software up-to-date. A security analyst will create and implement security policies, train employees on data security best practices, and report to management on whether these measures are working. The BLS reports that this is growing at 18%, which is much faster than average.
A solutions architect practices solution architecture (SA), which Gartner defines as “an architectural description of a specific solution.” According to Wikipedia, solutions architects usually work on the solution development team. “The solution architect translates requirements created by functional analysts into the architecture for that solution and describing it through architecture and design artifacts.” According to the BLS, jobs in this arena are growing faster than average, at 9%.
A hardware engineer (or computer hardware engineer) designs, creates, tests, troubleshoots and recommends non-software components such as routers, processors, circuit boards, chips, memory devices, servers, keyboards, printers, routers, and systems of the same. According to BLS, hardware engineering jobs are growing slower than average, at 3%. Most hardware engineers work in computer and computer system manufacturing companies.
Machine learning engineer
Everything a software engineer does, but with a focus on machine learning. In time, this role will likely work with every other function, as artificial intelligence and machine learning pervade everything. It may start with customer service or product development. Right now, much of the artificial intelligence software on the market offers a chatbot function. Or, it could begin with the data science role.
Cloud Datalab is an interactive data science workflow tool that makes it easy for developers and data scientists to explore, analyze, and visualize their data. With it, a machine learning engineer can build a model prototype. You’d use your smaller, locally stored dataset, then train your algorithm with a full dataset stored in the cloud.
If you’re looking to get into IT or grow your IT career, experts predict companies will increasingly seek out individuals with both hard and soft skills, because they’re best suited for projects that involve working closely with sales, support, and marketing.
“In collaboration between developers and CMOs or CFOs, project management skills, communication skills, and presentation skills will be in-demand by employers,” Tim Herbert, SVP of research and market intelligence at CompTIA, told TechRepublic.
What jobs did I miss? Let me know in the comments.
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