What does an AI & Data Science Specialist actually do?

by | Oct 28, 2022

One industry, many opportunities – that’s how you can describe the software industry. This is especially true for the MarTech sector. Here talents can find many exciting jobs especially in the fields of software development, but also in consulting and sales. For example the Specialist AI & Data Science.

Our AI specialist Fidel Gil had the opportunity to talk to the industry blog BASICthinking and present what he does on a daily basis for our MarTech company and what is particularly important to him.

The German interview appeared on BASICthinking on November 3, 2022.

Here you can read the complete interview in English and learn more about the profile of a Specialist AI & Data Science:

Fidel, you work as an AI & Data Science Specialist at the MarTech company matelso. Please describe to us in four sentences how you explain your job to new friends?

Sometimes that’s a real challenge, because I always have to elaborate a bit. To real laypeople, I always start by explaining what we do as a company: The MarTech company matelso develops software solutions for marketing departments in companies – but also for other areas such as sales or service. This includes our renowned Call Tracking technology, which helps marketers learn more about their customers and make their online marketing strategies more efficient. But above all, our new product, the matelso platform, with which we bring together (video) telephony, chat, mail and other direct communication channels between companies and their customers in one place. This data then enables better and more value-added business decisions.

Only then do I get to talk about my job: As an AI expert, I build applications for our platform that analyze the collected data in an automated way and identify opportunities in real time to improve the customer experience. So I make our system smarter.

What does a normal day as an AI & Data Science Specialist look like?

A normal day in the life of an AI specialist usually looks like this: 1. turn on the computer, 2. check on our agile planning tools, we use JIra, what is currently pending and 3. (like everyone else) read mails and check the calendar to see what else is planned. Then the work starts! And for me that means developing, setting up and optimizing data models, visualizing the data, finding trends or extracting information from larger data sets. These then flow into our algorithms and into the AI system. I also develop models that analyze and harness the concrete content of direct conversations via mail, (video) calls, chats or contact forms, and provide insights into people’s communication habits.

Alongside this, we also run the standards that every IT professional is familiar with: daily discussions and meetings in which we distribute goals and tasks and compare the results of the previous day. These are always a source of inspiration for us, as we exchange ideas and experiences here.

And what do you start the day with?

I think this is where I fall a little out of character among developers – they are often real coffee addicts. For me, it’s a little easier on the nerves: The first thing I do is get a fresh fruit juice from the fridge or make myself a cup of tea – depending on the weather. That way, I first gather energy and get good vibes for the day. Only then does my morning routine start.

What tasks fall under your purview?

When it comes to AI and how this technology should be integrated into our digital customer experience platform, I’m the contact person for the entire product management team. I play a key role in deciding which AI tools to use to solve specific challenges or implement new features in our system. And of course, I also program and integrate the applications, algorithms and data models.

Another important aspect of my job is to continuously demonstrate and evaluate the feasibility of our projects and potential risks in order to identify them as early as possible and to define and develop realistic solutions. In doing so, it is important to always keep an eye on the big picture and to keep all aspects of the platform in mind – all functionalities and elements must always mesh seamlessly. It’s simply not a good feeling when you design something that then disappears into a drawer again for technical, logical or computational reasons – or catches digital dust on your hard drive.

How do you personally define and interpret your job as an AI & Data Science Specialist?

In a nutshell: For me, the job is to obtain relevant data and derive value-creating significance for our customers from it. As simple as this sentence may sound, what lies behind it is quite challenging – in a positive and challenging way. For example, questions need to be answered such as: Where do we get this data from? Is the information representative of reality? Can we collect more data – and if so, where? And: Are there legal consequences for the handling of this concrete data? One of the most challenging tasks in my field is the collection of the relevant information in compliance with the guidelines. Because without it, all other aspects are practically doomed to failure.

Only then does my other expertise come into play: knowing what specific conclusions can be drawn from various data and how to make them actionable for our customers – in other words, analyzing and evaluating how they can be used to create value. There are a number of tools that can be used for this: graphics that visualize trends that are difficult to recognize, or models that can be used to classify objects or make predictions about future events. So it’s exciting what I deal with on a daily basis.

How does your job fit into the corporate structure? That is, who do you report to and who do you work with?

I report directly to our Head of Product Management, who is responsible for all three divisions of our product team – Base Services, Product and IT Infrastructure. The topic of artificial intelligence is so high profile for the development of our company because it reaches into all other areas of software development. That’s why I’m continuously working very closely with all other areas of the company to research and develop more use cases and technologies. I always have to be up to date on what my colleagues are up to for their modules and how I can support them with my work and expertise – and then how everything fits together.

Of course, the role of AI & Data Science Specialist is interpreted differently in each company. Which perspectives do you miss out on that are basically part of the job description?

Currently, I’m doing exactly what I imagined and what fits the job description for my profile. However, we are now on a development journey with our matelso platform, which is far from complete. I’m already looking forward to when we tackle the next milestone: Developing analysis and visualization tools that allow us to derive trends and predictions from the data we collect, and thus provide valuable behavioral forecasts. We’re not quite there yet, but only because we still lack the necessary amount of user data in the system. But that is only a matter of time. We’re on it and ready!

What do you enjoy most about your job?

I’m lucky with this job at matelso. I was able to start right here doing what I love and what I’ve been preparing for for so long. It was already one of my childhood dreams to work with computers. And now I’m not only using them, I’m also teaching them to perform a variety of complex tasks in an automated and intelligent way.

And the look on my colleagues’ faces as they watch in amazement and try out how the machines I’ve programmed do exactly what they’re supposed to, live and in color, gives me a great sense of pride in my work. It’s really indescribable.

What are you most grateful for?

It may sound like a cliché, but I’m really most thankful for being able to work on something I like and find fulfilling. And: that I work for a company that not only inspires with its vision, but also with an exceptional team and shows perspectives for the future – both technologically and personally.

In the digital industry in particular, there is often no longer a traditional apprenticeship. How did you get your job?

After completing my master’s degree at TU Kaiserslautern, I started looking for jobs in the field of Data Science & Machine Learning. And with my very first application, I landed a hit: at matelso. The rest is already history, so to speak. I think I got the job because I worked on the topic “Accent Based Speech Emotion Recognition for Human Robot Interaction” in my master’s thesis – specifically, I developed data models that enable a machine to read emotions from the human voice. This fit perfectly with the company’s previous profile as well as matelso’s motto “Voice Matters”. I also bring the right hands-on mentality to occupy this field, which is still relatively new for us, and to drive it forward together with my colleagues.

What advice would you give to a newcomer or interested career changer who also wants to become an AI & Data Science Specialist?

Before applying to a company, I recommend that newcomers build their own proof-of-concept (POC) with simple data sets – the data can be aligned with anything, such as a personal hobby. This should then be used to run a full pipeline – from data visualization and analysis to model training and testing. This is the best way to prove your complete expertise to a potential employer. For career changers, I would recommend the same. However, in this case, the data used should be based on the expertise acquired so far.

But the most important thing is: patience! And: practice, practice, practice! Much of the interaction between data, algorithms and models only becomes clear when you have run through the processes several times – not to say umpteen times. But that is an experience you must make. So, get on it!

If you like this job profile and are interested in growing our MarTech business with us you should have look at our career page.

Oct 28, 2022

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