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Lead Data Scientist
Salary

US$140000 - US$175000 per annum

Location

New York

Description

Data Scientist to cut their teeth in a data-first fast paced environment where they can maneuver their machine learning skills into strong business outcomes.

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Deep Learning Engineer
Salary

US$16000 - US$130000 per annum

Location

Boston, Massachusetts

Description

If you are interested in being the deep learning and AI expert on a team to lead out innovation and strategy...apply!

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Staff Machine Learning Engineer
Salary

US$10004 - US$300000 per annum + relocation, benefits, bonus

Location

New York

Description

Come lead AI efforts for R&D and infrastructure builds for one of the largest and most highly respected consultancies in the world.

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Deep Learning Engineer
Salary

US$140000 - US$165000 per annum + Amazing Benefits

Location

New York

Description

This is an opportunity for a Machine Learning expert with a strong focus on Deep Learning to take their talents to a cutting-edge biotech company.

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Principal Data Scientist
Salary

US$240000 - US$260000 per annum + Bonus + Benefits

Location

New York

Description

This is a technical leadership position in which you'll be building out a brand new team and platform for one of the fastest growing food/bev tech firms.

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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.

How Computer Vision Is Changing Healthcare

It may seem like every new decade we have a new technology to master. But what if we’ve flipped the script? Now AI has a new technology to master. I'm talking about Computer Vision. Just like humans learn to identify shapes into objects as children, so too, must the technologies we’ve created.  Why? Because autonomous vehicles need to know the difference between a tree and a person holding their grocery bags. Because manufacturing bots need to identify defective products before they go to the public. And in healthcare, Computer Vision can help us identify disease, help doctors make diagnoses, and dig deeper into what makes humans human. Three Trends to Watch  Already, systems have a 99% accuracy rate at emulating human sight. Like our own calculations when we “see” an object, machines will have to process, analyze, and understand the image as well. Thanks to Machine Learning and Neural Networks using pattern recognition, this is possible. What could this mean for the healthcare industry? Imaging Devices like X-Rays and MRI Machines will get smaller and more mobile. This trend will allow simpler imaging, quicker workflows, and live imaging for quicker diagnoses.Next Generation Phenotyping (NGP) allows predictive diagnoses using Computer Vision and Deep Learning to analyze data at the molecular level. Telemedicine to open greater access to your doctor rather than the traditional brick-and-mortar doctor’s office visit. Electronic Health Records (EHR) for a patient profile gives direct access to patient information and could reduce the cost of logistics and gaps in expertise. And Remote Patient Monitoring (RPM) allows for real-time medical decisions to flow between patient-doctor without the ubiquitous red tape traditional medicine brings. Recent advancements in visual technologies will have a strong impact in a variety of industries. But it’s in the healthcare industry, Computer Vision, AI, and IoT will particularly shine as the technologies converge for greater progress in healthcare.  AIoT and Image-Based Data Converge for Improved Outcomes  There are such a variety of uses for Computer Vision in medicine, it can be hard to imagine where it can't be used. When you consider how much medical data is image-based such as mammograms, MRIs, CT Scans, X-Rays, and Echocardiograms, it’s easy to see how patients will benefit.  Imagine getting an early diagnosis to stop the spread of cancer or stopping dementia in its tracks. These systems alone can assist with surgery, identify problems early, and more. When your medical team of institutions, providers, and patients have access to these systems and truly partner, then this becomes the future of healthcare.    Add to improvements in computer vision, the rapidly advancing technologies of AI, and IoT and watch how quickly problem-solving scenario outcomes improve across all industries. Much like the last convergence of mobile phones and the internet, AIoT will usher in a new era of human history in similar fashion. Risk and Reward of AIoT, ML, and Computer Vision With greater advancement, comes greater risk and reward. As sensors and connectivity multiply across devices and industries, renewed focus should include privacy and security. Such large volumes of Data, even within the healthcare industry, can be targets for hackers as well as government entities. It may seem strange to consider this in the light of the healthcare vertical, but imagine the repercussions of denials due to medical issues or the inverse of identity theft.  The convergence of AIoT and Computer Vision technologies use complex algorithms for predictive analytics. Add Machine Learning into the mix and watch workflows streamline, simplified problem-solving unfold, and improved reliability and sustainability of data capture and how it can enhance an organization’s processes.  In the cumbersome world of healthcare and its institutions, Computer Vision, AI, IoT, and Machine Learning offer a simpatico balance between patient and provider that flips traditional healthcare upside down. Advancements within the last few years and in the coming decade are primed to bridge the gap between patient and provider. But it’s going to need Data professionals who have a passion for the industry and can guide these technologies to the next stages in their development. The Computer Vision industry is supercharged and is expected to reach $48.6 billion by 2022. Ready to see where the latest technologies can take you? If you’re interested in Computer Vision, Big Data, and Analytics, Robotics, and more, we may have a role for you.  Check out our current vacancies or get in touch with one of our expert consultants to learn more.  For our West Coast Team, call (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.  

Mairead Holt

Mairead Holt

27. February 2020

Machine Learning and Customer Experience for Business Scalability

Over the last four decades, we’ve feared change. Technophobia. Cyberspace. Smart devices. AI, Robotics and Automation. Each of these transformative shifts have changed our lives in one way or another. But there is a new, unexpected and desperately needed change already in play; putting the human back in our lives.  Human Resources. Human-centric customer service. Humans in cooperation and collaboration with smart technology. Both in B2B and B2C businesses, putting the human back in focus is imperative to success.  Consider Netflix. How it began, how it’s evolved, and how its efforts are seemingly leading the way for next gen personalization. Think: If you like this, then you may like (insert service or product here). Amazon does much the same. Putting the Human Element Back in CX When you call customer service with a concern or problem. What happens? Either there’s no phone number at all and you’re forced to send an email which you hope gets read by a person. Or if you do call, you push buttons trying to figure out which branch of the tree will get you to the correct person.  Chatbots have been one answer but they really only alleviate acknowledgement. We’ve all called a customer service number and spoken to two or more people about our issue. Bill Paterson, EVP of Salesforce, suggests a four-point, human-centric customer service engagement strategy, to help solve the problem.  In addition, his article takes a deeper dive into putting the human back in customer service. At the heart of the matter is putting Emotional Intelligence, care, and empathy back into the equation. Technology may be how people reach out, but it’s a human they want to speak to and connect with. When the two are paired, there’s a much better chance of success. And repeat customers. Pairing Machine Learning with a Human-Centric Touch While strategies and metrics still have a big role to play, there are other ways to measure customer success. Data gathered from your customers will only get you so far, but the human element, the human connection, supported by technology, is the next shift in Digital Transformation.  Machine Learning models can help predict what customers will want or need, but meaningful customer relationships are just as vital. It’s this pairing which can generate great service and scalability of today’s modern business. Though there is a strong underpinning of engineering components in building models, only a portion involves code. Much of the effort goes into the pipeline and workflow systems and infrastructure. It’s at this systems level, Data Scientists can focus on design and implementation of production. This strategy ensures that before building good models, a good foundation must be laid. One portion of this workflow has been called the ‘art of Machine Learning’. The ‘Art’ of Machine Learning  Data Scientists and Machine Learning Engineers have any number of ways to solve a problem. Dealing with such vast amounts of Data within a model is not unlike determining how to scale for a website which needs to handle large fluctuations in web traffic. The nuances of technology within the realm of human experience is an artform. Though in the future, most engineering challenges will be automated and open-source will be a go-to framework. As tools improve and ETL processes improve, ML Engineers and Data Scientists will get the opportunity to focus more on models and less on systems. But beyond the artform of experimentation and intuition is the growing trend for soft skills in tandem with technical skills. Those who can lead a technical team, who can communicate to non-technical professionals, and still have the Emotional Intelligence to navigate the human psyche. It’s these individuals who will be ready for the next step in leading businesses into the next generation of customer service.  Ready to take the next step in your career? Take a look at our current vacancies or contact one of our expert 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.  

Leah Topham

Leah Topham

20. February 2020

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