Computer Vision Jobs in New York

At Harnham, we understand the importance of a strong Computer Vision team who can develop bespoke algorithms and continuously innovate. We make it our mission to utilize our vast Data & Analytics knowledge to deliver a professional and quality experience.

View Computer Vision Jobs in New York here now.

Latest Jobs

Salary

US$200000 - US$220000 per annum

Location

New York

Description

This medical imaging start up is making huge advancements for the industry

Salary

US$190000 - US$210000 per annum

Location

New York

Description

This company invest huge amounts of money into using the latest technologies, methodologies and innovate their approach to the Computer Vision space.

Salary

US$190000 - US$210000 per annum

Location

New York

Description

Looking for a Director of Artificial Intelligence for a medical imaging start up in the New York City area

Salary

US$175000 - US$185000 per annum

Location

New York

Description

Do you want to use your Computer Vision expertise to assist the prevenetion of a disease that is currently impacting the public internationally?

Salary

US$160000 - US$180000 per annum

Location

New York

Description

This company is changing people's lives with AI

Salary

US$180000 - US$225000 per annum

Location

New York

Description

This is your opportunity to lead one of the best teams in the medical imaging industry!

Salary

US$185000 - US$210000 per annum

Location

New York

Description

Recognized globally for their innovative approach to medical imaging, this established leader has remained on the cutting edge of the industry for decades!

Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

Computer Vision in Our Day-to-Day Lives

We make micro adjustments every day to what we wear, how we shop, and how we drive. Our healthcare and industrial verticals are working with AI and Computer Vision to enhance our experiences from the user to the professional. There are a variety of computer vision applications to make life easier, more efficient, and safer. In other words, our computers have eyes. Every industry, it seems, is now touched by Computer Vision. From retail to healthcare to agriculture to banking, AI technology combines with deep learning and machine learning to help computers “see” where a car goes, an individual’s health, and what outfit might look best for any given outing. So, let’s take a look at some of the industries currently using Computer Vision. AUTOMOTIVE Human error and distractions often lead to car accidents and fatalities. According to the WHO, it’s estimated traffic accidents will be the seventh leading cause of death by 2030. To help alleviate this prediction, there is work being done on a self-driving car with sensor technology. Though autonomous cars have been tried before, this next incarnation has worked to ensure it can detect not only other cars and other large obstacles, but also pedestrians and cyclists at a distance. As it navigates through the streets autonomously, it follows traffic regulations as well as detect hand signals, and more. Efforts to train the vehicles use deep learning to predict, plan, and map its way through various scenarios. HEALTHCARE The advent of Computer Vision in technology has been a boon to the industry. It can help determine conditions of illness, reduce or eliminate misdiagnoses, and can even monitor blood loss during medical situations.  Captured images on items such as surgical sponges can be processed using Computer Vision using Machine Learning. In comparison with the human eye, the computer’s estimates were more accurate.  RETAIL  Retail has been at the forefront of many changes within the tech industry. And now, as online shopping, e-commerce, and virtual events take over traditional venues and brick-and-mortar stores, even the task of trying on clothes has gone virtual. From a virtual mirror which uses Computer Vision to help identify what outfit looks best. What may be most appropriate in what situation. Something like a movie montage, but in real time for a real person.  Retail takes things a step further by stepping up security. Using Computer Vision, retail security apps can monitor what is being recorded, what has been taken from shelves, and items being fake scanned. This information and knowledge can lead to reduced theft and other losses in stores. While other industries such as banking and agriculture have also seen a rise in Computer Vision, it’s the above which we might see in our day-to-day lives sooner rather than later. ONE FINAL THOUGHT Business processes have shifted online, looking for your next job has become more daunting than ever before. But here’s the good news. Everyone’s on the same page. Leaders, hiring managers, recruiters, and prospective employees are all navigating a new way of doing business and finding talent to keep those businesses running. In the wake of work-from-home policies, remote working, and the shifting landscape of working outside the office, technology, and particularly biotechnology careers are prime opportunities to both gain increased knowledge in your chosen field or begin your career path.  If you’re interested in Big Data & Analytics or other Data professional opportunities, check out our current vacancies or contact one of our recruitment consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Why You Should Always Be Learning In Data Science: Tips From Kevin Tran

Last month we sat down with Kevin Tran, a Senior Data Scientist at Stanford University, to chat about Data Science trends, improvements in the industry, and his top tips for success in the market.  As one of LinkedIn’s Top Voices of 2019 within Data & Analytics. his thoughts on the industry regularly garner hundreds of responses, with debates and discussions bubbling up in the comments from colleagues eager to offer their input.  This online reputation has allowed him to make a name for himself, building out his own little corner of the internet with his expertise. But for Tran, it’s never been about popularity. “It’s not about the numbers,” he says without hesitation. “I don’t care about posting things just to see the number of likes go up.” His goal is always connection, to speak with others and learn from them while teaching from his own background. He’s got plenty of stories from his own experiences. For him, sharing is a powerful way to lead others down a path he himself is still discovering.  When asked about the most important lesson he’s learned in the industry, he says it all boils down to staying open to new ideas.  “You have to continue to learn, and you have to learn how to learn. If you stop learning, you’ll become obsolete pretty soon, particularly in Data Science. These technologies are evolving every day. Syntax changes, model frameworks change, and you have to constantly keep yourself updated.”  He believes that one of the best ways to do that is through open discussion. His process is to share in order to help others. When he has a realisation, he wants to set it in front of others to pass along what he’s learned; he wants to see how others react to the same problem, if they agree or see a different angle. It’s vital to consider what you needed to know at that stage. Additionally, this exchange of ideas allows Tran to learn from how others tackle the same problems, as well as get a glimpse into other challenges he may have not yet encountered.  “When I mentor people, I’m still learning, myself,” Tran confesses. “There’s so much out there to learn, you can’t know it all. Data Science is so broad." At the end of the day, it all comes down to helping each other and bringing humanity back to the forefront. In fact, this was his biggest advice for both how to improve the industry and how to succeed in it. It’s a point he comes back to with some regularity in his writing. “It doesn’t matter how smart you are, stay humble and respect everyone,” one post reads. “Everyone can teach you something you don’t know.” Treating people well, understanding their needs, and consciously working to see them as people instead of numbers or titles—this, Tran argues, is how you succeed in the business. To learn and grow, you must work with people, especially people with different skills and mindsets. Navigating your career is not all technical, even in the world of Data. “The thing that cannot be automated is having a heart,” he tells me sagely. Beyond this, Tran stresses the need for a solid foundation. The one thing you can’t afford to do is take shortcuts. You have to learn the practicalities and how to apply them, but to be strong in theory as well.  Understanding what is happening underneath the code will keep you moving forward. He compares knowing the tools to learning math with a calculator. “If you take the calculator away, you still need to be able to do the work. You need the underlying skills too, so that when you’re in a situation without the calculator, you can still provide solutions.” By constantly striving to collaborate and improve, Tran believes the Data industry has the best chance of innovating successfully.  If you’re looking for a new challenge in an innovative and collaborative environment, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

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