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Data scientists: don’t be afraid to explore new avenues

I’m a native French data scientist who cut his teeth as a research engineer in computer vision in Japan and later in my home country. Yet I’m writing from an unlikely computer vision hub: Stuttgart, Germany.

But I’m not working on German car technology, as one would expect. Instead, I found an incredible opportunity mid-pandemic in one of the most unexpected places: An ecommerce-focused, AI-driven, image-editing startup in Stuttgart focused on automating the digital imaging process across 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 diverse job opportunities while being known as hubs for some specialties.

While there has been an uptick in fully remote jobs thanks to the pandemic, extending the scope of your job search will provide more opportunities that match your interest.

Search for value in unlikely places, like retail

I’m working at the technology spin-off of a luxury retailer, applying my expertise to product images. Approaching it from a data scientist’s point of view, I immediately recognized the value of a novel application for a very large and established industry like retail.

Europe has some of the most storied retail brands in the world — especially for apparel and footwear. That rich experience provides an opportunity to work with billions of products and trillions of dollars in revenue that imaging technology can be applied to. The advantage of retail companies is a constant flow of images to process that provides a playing ground to generate revenue and possibly make an AI company profitable.

Another potential avenue to explore are independent divisions typically within an R&D department. I found a significant number of AI startups working on a segment that isn’t profitable, simply due to the cost of research and the resulting revenue from very niche clients.

Companies with data are companies with revenue potential

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

Leveraging such customer engagement data benefits everyone. You can apply it towards further research and development on other solutions within the category, and your company can then work with other verticals on solving their pain points.

It also means there’s massive potential for revenue gains the more cross-segments of an audience the brand affects. My advice is to look for companies with data 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 yet introduced such a system, or they don’t have someone with the skills to properly utilize it. If you finding a company isn’t willing to share deep insights during the courtship process or they haven’t implemented it, look at the opportunity to introduce such data-focused offerings.

In Europe, the best bets involve creating automation processes

I have a sweet spot for early-stage companies that give you the opportunity to create processes and core systems. The company I work for was still in its early days when I started, and it was working towards creating scalable technology for a specific industry. The questions that the team was tasked with solving were already being solved, but there were numerous processes that still had to be put into place to solve a myriad of other issues.

Our year-long efforts to automate bulk image editing taught me that as long as the AI you’re building learns to run independently across multiple variables simultaneously (multiple images and workflows), you’re developing a 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 who can.

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

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Google launches its AI-powered jobs search engine

 Looking for a new job is getting easier. Google today launched a new jobs search feature right on its search result pages that lets you search for jobs across virtually all of the major online job boards like LinkedIn, Monster, WayUp, DirectEmployers, CareerBuilder and Facebook and others. Google will also include job listings its finds on a company’s homepage. The idea here is to give… Read More

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Glassdoor raises $40M, valued around $1B, for a job search platform with peer reviews

GLASSDOOR THUMBNAIL As the job market becomes more competitive in some industries and unemployment holds steady and even drops in certain regions, job site Glassdoor is reaping some of the rewards. The company — which helps people look for jobs and research companies that interest them based on feedback from others — has raised another $40 million in funding, a Series H round that values the company… Read More

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How to quit your job the right way

iquit It’s too easy to slip into melancholy and gloom. Corporations want to ultimately fire you, whether you like your job or not. Their entire purpose is to create and squeeze the efficiencies out of you until you drop dead or are no longer needed. Know when to jump. Read More

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How Mobile Apps Are Transforming The Job Search

mobile-cv-resume1 Searching for a job is just like dating, banking or procrastinating on chores until someone else does them: It’s something we all have to do. So why shouldn’t the job search be the basis for mobile apps, like those other adult obligations? Over the past couple of years, it has. As 2015 turns to 2016, the job search is now squarely the business of mobile technology, with the tedium… Read More

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Connectifier Raises $6M More For Its AI-Based Recruitment Search

magnifying glass, explore A couple of weeks ago, LinkedIn announced a new version of its recruitment product, giving HR teams the ability to look for new hires that most closely match the profiles of employees they already know and like. But LinkedIn was not the first to use search technology, machine learning and so-called “entity recognition” to update and improve the hiring process. A much… Read More

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