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Principal Data Engineer
Salary

US$170000 - US$180000 per annum + Additional Benefits

Location

New York

Description

A NYC-based health-tech start up are looking to bring on a seasoned professional as their Principal Data Engineer!

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Machine Learning Production Engineer
Salary

US$140000 - US$160000 per annum + Base Salary

Location

Boston, Massachusetts

Description

This labor market expert business is looking to bring on a Machine Learning Production Engineer to their Boston, Massachusetts headquarters.

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Senior Data Architect and Engineer
Salary

US$150000 - US$170000 per annum + Additional Benefits

Location

New York

Description

Join one of our top clients in health tech in NYC to build out their data platform to enable Machine Learning!

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VP Data Governance
Salary

US$225000 - US$250000 per annum

Location

New York

Description

Do you want to join one of the largest Asset Management Managers in the world?

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Sr. Director AWS Data Architect
Salary

US$200000 - US$240000 per annum + Additional Benefits

Location

Boston, Massachusetts

Description

A global biopharma industry leader is looking to bring on a Sr. Director of AWS Data Architecture to join their Boston office.

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Principal Data Architect - Biotech Leader
Salary

US$170000 - US$200000 per annum + Additional Benefits

Location

Boston, Massachusetts

Description

A global biopharma industry leader is looking to bring on a Principal Data Architect to join their Boston headquarters

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Senior Machine Learning Engineer
Salary

US$170000 - US$180000 per annum

Location

New York

Description

Do you want to join a high-performance advertising platform driven by state-of-the-art machine learning algorithms?

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Director of Data Engineering
Salary

US$180000 - US$200000 per annum + Additional Benefits

Location

New York

Description

A NYC healthcare leader is looking to bring in a Director of Data Engineering to join their team!

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Senior Machine Learning Production Engineer
Salary

US$140000 - US$160000 per annum + Base Salary

Location

Boston, Massachusetts

Description

This labor market expert business is looking to bring on a Senior Machine Learning Production Engineer to their Boston, Massachusetts headquarters.

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Head of Data Governance - Real Estate Start-up
Salary

US$220000 - US$250000 per annum + Additional Benefits

Location

New York

Description

A global industry leader is looking for a Head of Data Governance to join their real estate branch in NYC!

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Head of Data Governance - Real Estate Start-up
Salary

US$220000 - US$250000 per annum + Additional Benefits

Location

Newark, New Jersey

Description

A real estate business is looking for a Head of Data Governance to join them in Newark!

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Lead Data Engineer
Salary

US$160000 - US$180000 per year

Location

New York

Description

Are you looking to join rapidly growing tech business where you can build an engineering team from scratch?

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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.

Blockchain Technologies Find Fuel in the Life Sciences Industry

When Ford first introduced the assembly line, he could only imagine how it would affect the automotive industry. But what about how it could affect supply and demand within the life sciences industry? Automotive and similar factories have been converted before to help build items most needed. Not the least of which, today, is to help supply those in the life sciences industry with the PPE and medical devices they need. Demand is high. Supply is not. Enter blockchain technologies.  As health systems become overburdened and disruptions to ‘normal’ life occur on a global scale, it’s important to ensure critical resources are prioritized. So, what can businesses do to help ensure supply and demand are met in not only these critical times, but for the future. FIVE WAYS TO ENSURE SUPPLY MEETS DEMAND When it’s difficult to supply even the most in demand products, it’s time to take an assessment of various scenarios. These scenarios can help leaders predict what and when they’ll need certain products and critical items. Assess your scenario within the framework of increased disruption.What are your capabilities?Identify the most immediate needs to meet, any risks to be aware of, and take action.Determine any structural changes you’ll need to make.Prepare to pivot. Be aware you may be in a continuous cycle of determining risk, assessing where you are and need to go, any configurations you’ll need to make to get there, and any operational procedures to improve and move forward. By assessing, prioritizing, and visualizing, companies are able to craft a clearer scope of vision. The scenarios created can offer insight into key pieces of planning to help mitigate disruptions of supply chain processes. This crisis will have long-lasting effects and implications from how we work to how we assure supply and demand. It’s in these strange crosshairs, the life sciences industry finds itself at the center of this pandemic, and at the same time is the life force which has given blockchain technologies fuel to improve. No matter where you are on the spectrum of supply chain technology, there is calculated risk to every decision. Just because we’re easing restrictions now, doesn’t mean there won’t be an about face in the next few months, and what companies do between now and then is critical. Supply is already short. Now is the time to take immediate action to help mitigate risk for patients, providers, your clients, and your communities WHAT TO DO NOW AND HOW TO PREPARE FOR THE FUTURE The scale of risk is unlike any leaders have seen in recent years. Its speed adds to the uncertainty as numbers rise, decisions change, and most are left wondering what’s next. Businesses who respond quickly and confidently can help to alleviate some uncertainties, but can craft a plan crucial to understanding the complexities of blockchain within the industry. Strong data, analysis, predictive modelling can help to anticipate any further or potential disruption. Taking these steps can help make businesses more resilient in the future and also help them manage future challenges. It’s integral to have strong, responsive, and resilient risk management capabilities. To do this, your business will want to ensure their capabilities are technology-led platforms which support analytics, machine learning, and artificial intelligence. Whether you’re mitigating risk, preparing an assessment, or determining your capabilities, it’s important to ensure you’re transparent. We are all in this together. Even in business. Transparency builds trust as does assuring supply and demand by mitigating risk. It’s these things which will soon become the basics of business protocols. Business processes have shifted online, looking for your next job has become more daunting than ever before. But here’s the good news. 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 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 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.  

Karla Guerra

Karla Guerra

28. May 2020

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. 

William Reichert

William Reichert

19. March 2020

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