Tuesday, September 21, 2021
HomeTechnologydon’t be afraid to explore new avenues – TechCrunch

don’t be afraid to explore new avenues – TechCrunch

don’t be afraid to explore new avenues – TechCrunch

I am a data scientist of French origin who cut his teeth as a computer vision research engineer in Japan and later in my home country. Yet I write from an unlikely computer vision center: Stuttgart, Germany.

But I’m not working on German automotive technology, as you might expect. Instead, I found an incredible opportunity in the midst of a pandemic in one of the most unexpected places: an e-commerce and AI-focused image editing startup in Stuttgart in Stuttgart has turned up. focused on automating the digital imaging process in all retail products.

My experience in Japan taught me the difficulty of moving to a foreign country for work. In Japan, having a point of entry with a professional network can often be necessary. However, Europe has an advantage here thanks to its many accessible cities. Cities like Paris, London and Berlin often offer various employment opportunities while being known as hubs for certain specialties.

While there has been a slight increase in fully remote jobs thanks to the pandemic, expanding the scope of your job search will provide more opportunities that match your interests.

Look for value in unlikely places, like retail

I work in the tech spin-off of a luxury retailer, applying my expertise to product images. Approaching it from a data scientist’s perspective, I immediately recognized the value of a new app for a very large and established industry like retail.

Europe has some of the best-known retail brands in the world, especially for clothing and footwear. This rich experience provides an opportunity to work with billions of products and billions of dollars in revenues to which imaging technology can be applied. The advantage of retail businesses is a constant flow of images to process which provides a playing field for generating income and possibly making an AI business profitable.

Another potential avenue to explore are independent divisions usually within an R&D department. I have found a significant number of AI startups working in a segment that is not profitable simply because of the cost of research and the resulting revenue for very niche clients.

Businesses with data are businesses with revenue potential

I was particularly drawn to this startup because of the potential access to data. The data itself is quite expensive, and a number of companies end up working with a finite set. Look for companies that engage directly at the B2B or B2C level, especially retail or digital platforms that affect the front-end user interface.

Everyone benefits from leveraging this customer engagement data. You can apply it to further research and development on other solutions in the category, and your business can then work with other verticals to resolve their issues.

It also means that there is huge potential for earning more revenue from the brand affects cross-segments of an audience. My advice is to look for companies whose data is already stored in a manageable system for easy access. Such a system will be beneficial for research and development.

The challenge is that many companies haven’t introduced such a system yet, or don’t have someone with the skills to use it properly. If you find that a company is unwilling to share in-depth information during the courtship process or has not implemented it, consider the opportunity to introduce such data-driven offerings.

In Europe, the best bets are to create automation processes

I have a soft spot for start-ups that give you the ability to build basic processes and systems. The company I work for was in its infancy when I started, and it was working on creating scalable technology for a specific industry. The issues the team was tasked with resolving were already being resolved, but there were still many processes to be put in place to resolve a myriad of other issues.

Our year-long efforts to automate mass image editing have taught me that as long as the AI ​​you build learns to operate independently on multiple variables simultaneously (multiple images and workflows), you are developing technology. that does what established brands haven’t been able to do. In Europe, there are very few companies doing this and they are hungry for talent that can.

So don’t be afraid of a little culture shock and take the plunge.





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