Explain 5 New Tech Jobs To Your Grandma


Along with new technologies, new jobs are popping up. Those working in the tech field know the struggle: how do you explain them to your grandmother? Don’t worry, you’re not alone. Here’s a list of 5 tech jobs that are super hard to explain to your grandmother.
by: Karim Youssef & Misch Strotz
photo: Alex Harvey ???????? on Unsplash
SOCIAL MEDIA MANAGER

“So you get paid for being on Facebook, right?” Wrong!

The social media manager is probably the most misinterpreted job in the modern world. Simple on the surface, this job is super challenging to execute.

The social media manager is in charge of a company’s social media marketing and advertising operations.

They are the curators of the company’s different social media channels like Facebook, Instagram, Twitter, Pinterest and YouTube, and the list is growing.

The objective seems rather simple: communicating a company’s brand to convert viewers to customers. Achieving this objective, however, requires a combination of many skills and the ability to adapt to new and ever-evolving tools.

Social Media Managers’ tasks range from long-term planning like developing a social media strategy for the brand, defining and refining the look and feel of the social media channels, and running paid advertising campaigns, to daily tasks like content creation, making posts or responding to comments and messages.

In addition to planning, monitoring and moderating different channels on a daily basis, the Social Media Manager must understand data-science to improve campaign performance and grasp customer behavior. This is crucial since the Social Media Manager decides not only which social media platform to be on, but also which ones are not performing and thus not useful for the company.

Tasks of a Social Media Manager
> Monitoring, moderating and responding to audience comments
> Managing partnerships with other brands
> Social media marketing and advertising
> Monitoring and optimizing performance
DATA SCIENTIST

No lab rats or chemical explosions here, just a safe job in front of the PC. One could argue that a data scientist is a modern-day Alchemist, especially when thinking about data being the new gold.

A good data scientist knows how to gather and combine different data-sets in order to extract meaningful insights and translate them into actionable tasks to increase business growth and improve online businesses. They’re looking for the digital gold nuggets.

They combine statistical tools and methods with machine-learning to collect, clean and mung data. Data munging or Data wrangling describes the process of transforming and mapping data, thus preparing it for further uses like data visualization, data aggregation or machine-learning.

This process requires persistence, statistical understanding and software engineering skills to find biases in the data and optimize machine-learning software, for example.

The data is then analyzed with the intention of understanding, for example, customer behavior in order to make data-driven decisions. Therefore, the data scientist’s on testing, machine learning (for decision making) and data-related subjects.

Tasks of a Data Scientist
> Interpreting data to discover solutions and opportunities
> Determining relevant data sets and variables
> Collecting, cleaning and combining structured and unstructured data
> Developing algorithms to mine big data
> Analyzing data to identify patterns and trends
CLOUD ARCHITECT

The “cloud” is one of the buzz words that has emerged from the internet. Speaking in analogies: clouds bring rain that waters plants. They’re the backbone of today’s server farms, and these farms need architects. Not only in a literal sense, but also in the digital space.

Thus, the cloud architect is in charge of a company´s cloud computing strategy, infrastructure and network, as well as the maintenance and monitoring of server-related processes. They need a strong understanding of these server technologies. Designing and migrating cloud-based applications is just one of the many tasks they need to be able to perform.

The cloud architect also consults companies and third parties to supervise the ideal usage of the cloud systems in place, as well as potential opportunities.

This job often requires experience with multiple programming languages to manage and integrate tools and services.

Tasks of a Cloud Architect
> Developing and coordinating cloud architecture
> Developing a cloud strategy and coordinating the adaptation process
> Assessing applications, software and hardware
> Monitoring, maintaining and troubleshooting of the cloud network
> Maintaining network security
VIRTUAL ASSISTANT

Everybody has been through periods of their lives where 24 hours just wasn’t enough time to take care of everything. How amazing would it be if you could hire a person to do certain repetitive, time-consuming tasks?

A virtual assistant does just that. Like the name implies, it is an assistant operating via the internet that assists clients in their day-to-day activities, allowing them to focus on the bigger picture.

Don’t confuse this actual job with “Virtual assistant software,” which are programs that perform similar tasks autonomously, but often with very limited capabilities.

The tasks of a human virtual assistant vary from client to client and can include things like booking flights, contacting potential investors or any other task that can be executed remotely.

Usually working as freelancers, virtual assistants do just about anything they’re asked within the legal framework to make the client’s professional and private life easier. While their roles can be very diverse, they are often hired to support specific tasks, e.g. helping with research, filing reports, administrative tasks or managing social media accounts.

Overall, the main responsibility of the virtual assistant is to make the business more productive, allowing busy bees to offload some tasks to someone else and focus on more important tasks.

Tasks of a Virtual Assistant
> Managing emails and booking appointments
> Managing social media
> Creating content
> Conducting over research and contacting clients
> Handling administrative tasks
AI ENGINEER

Artificial intelligence and machine learning are words that many people have heard over the past months, but only very few people actually understand how artificial intelligence works under the hood. According to the New York Times, there are fewer than 10,000 qualified people working in AI worldwide, and universities are only producing around 100 people each year.

Don’t worry about your Grandma too much. This job is widely misunderstood among young people because the definition of what real artificial intelligence is varies widely. A recent report from London-based venture capital firm MMC Ventures found no evidence that AI was part of the products offered by around 40 percent of Europe’s 2,830 AI startups.

For companies that wish to implement machine learning and AI into their business framework, the AI engineer is at the center of their project. AI engineers have a strong understanding of data science, applied research and coding, and today typically specialize in machine learning or the development of neural networks. While running operations related to machine learning, they are responsible for managing the necessary infrastructure and data.

In addition to actually developing code, they often supervise AI product managers and business stakeholders to help them understand the opportunities and limitations of AI when planning new products.

A lot of these new jobs are perfect for digital nomads, meaning that many of them can be executed entirely remotely. No need to drive to the office every day, just grab a laptop and get things done. And hey, no matter how complicated they seem, maybe one of these new jobs is the perfect fit for you.

Tasks of an AI Engineer
> Setting up and managing AI development and production infrastructure
> Identifying machine learning opportunities and new training datasets
> Building AI models from scratch and helping product managers and stakeholders understand results
> Bringing AI models into production
> Creating APIs and helping business customers put AI models into operation

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