Life Science Analytics

What We Do

From Biotech and Pharmaceutical firms, to Research and Academia, we help the best Life Science Analytics talent find rewarding careers.

With cutting edge sequencing techniques providing more insights into data than ever, every day sees the rise of new technology and new start-ups to accompany it. Now that technology allows for a person’s entire genomic data to be processed within a day, there is a huge demand for those who can analyze information and apply insights to advances in Healthcare.

Whether you’re learning about living systems, creating algorithms to interpret DNA, or building real—world models to interpret your findings, our Life Science team understand the importance of placing the right talent in the right business.

how We Do it

Our specialist Life Science Analytics team’s unique understanding ensures exceptional service throughout the entirety of your job search or recruitment process.

We have developed an in-depth knowledge of the market, as well as the different types of organizations that we work with, and their diverse requirements.

By understanding the full picture, are we able to deliver staffing solutions that ensure the very best outcome for everyone we work with.

What sets us apart?

Whatever your specialism, we have the knowledge, the network, and the required drive to find the best possible result.

Our specialty is matching highly experienced and skilled talent, with world leading organizations and forward-thinkers who see the opportunities that Life Science Analytics offer.

We have a unique understanding of this arena and excellent relationships with some of the best organizations around. If you’re hoping to change career or are looking for the next member of your team, we can help you.

Latest Jobs

Salary

US$170000 - US$200000 per year + BENEFITS

Location

San Francisco, California

Description

Create a new generation of immuno-oncology therapeutics with this start up!

Salary

US$150000 - US$180000 per year + BENEFITS

Location

San Francisco, California

Description

Join a passionate biotech team in paving the way for the future of electronic health records

Salary

US$150000 - US$180000 per year + BENEFITS

Location

San Francisco, California

Description

Use your informatics skills to impact patient health. This mid-size biopharma company is looking for a leader to join their team!

Salary

US$125000 - US$150000 per year + EQUITY, BENEFITS

Location

South San Francisco, California

Description

Want to help defeat widespread metabolic diseases utilizing the latest technology at the intersection of biology and data science?

Salary

US$220000 - US$250000 per year + BENEFITS

Location

San Francisco, California

Description

Use both your expertise in biology and machine learning to change how therapeutics are developed.

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.

The Landscape Of The Emerging Biotech Industry And Data Science In HR

One of the latest technologies to emerge to disrupt an industry is Biotechnology. This industry is booming and is no longer confined to universities and research labs. These are the people who build drugs to combat diseases and are expected to comprise a quarter of the market by 2020, less than 6 months from now. So, what does that mean for HR? A Streak of Lightning Across the Life Sciences Biotechnology has grown at an impressive 5% across revenue streams, number of businesses, and number of employees. It is a lightning streak across the Life Sciences and shows no signs of slowing down. In a field expected to corner a quarter of the market as soon as next year, it’s important to have the right people in place. We already know there is a skills gap in the Data Science industry, but the predictions show it's time to upskill the current workforce. Companies will need people who have the right skills and can implement them into action. Technology has disrupted every industry and R&D is no different. This means work life is being redesigned as the Biotech industry demands not only technical and Life Science skills, but also more human skills. The challenge is ensuring businesses understand the impact these technologies will have now, and in the future. If they don’t act, their business could stagnate. It’s important executives see applications at work and implement the changes needed to “keep up with the Joneses” of the tech world. In other words, leaders must find a balance between rapidly advancing technologies and the human insight those technologies provide. Redesign Your Ideal Candidate While digital and analytical skills should be standard for just about any industry, there are other things to consider when interviewing. Hiring Managers, recruiters, and businesses over all, will also be looking for the following ImaginationCuriosityEmotional Intelligence You may not be a doctor exactly, but do still have to deal with people. Organizations will need employees who not only ask why, but take the steps to find the solution, and at the same time can navigate an emotionally charged project such any client-facing research when discussing cancer therapies, for example. Transferable Skills are Key If you pivot well and can learn and understand projects on a dime, then this is a good industry for you. If you’re a business and you want to scale up quickly, it may be best to upskill or reskill, your current employees. With talent scarce in the market, this may be the best solution for you. Building transferable skills, being flexible, and having a strong academic background will help, too. Companies actively working to skill their workforce to work with Machine Learning and Artificial Intelligence technologies are just a few of the trends coursing through the Biotech industry. Add to that the myriad researchers, corporations, and governments focused on combatting diseases using available technologies, and its expected growth could make it one of the most efficient and prosperous industries in the digital landscape. Making HR Data Work for You Businesses are using HR data to see how they can get a deeper understanding of employees as a whole. Are they overwhelmed? Do they need to rest? Do they need to be challenged? Are they bored? How can you, as a business, help them to enhance not only their performance, but that of your business. Finding exciting new recruitment channels Much like you know to go where your customers are, the same holds true today when you’re trying to fill a role. Focus your efforts are on where the talent is, don’t wait for them to come to you. And with the average recruitment process averaging 71 days, the name of the game is “don’t delay” for your perfect candidate may have already moved on to something else. Engaging and motivating staff Think of your employees as internal customers. Engage with them as you would any customer, and make your employee a partner in your vision. Now, it’s easier than ever to measure, improve, and boost employee satisfaction using available data and analytics options. Making learning and development more effective Learning has become a highly personal, adaptive tool offering course selections. Because online courses are so prevalent, it’s much easier for an employee to learn a new skill without time and expense away from the office. The digital transformation of this space shows how data can be used in corporate learning and professional development opportunities. This is where you’ll want to focus some of your energy should you need to upskill or reskill your employees to keep up with demand. Are you a business who knows you’re ready to scale up and hire a data professional? We have a strong candidate pool and may have just the person you need to fill your role. Are you a candidate looking for a role in big data and analytics?  We specialize in junior and senior roles. Check out our current vacancies or contact one of our recruitment 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, call (212) 796 - 6070 or send an email to newyorkinfo@harnham.com.

Battle Royale: Computational Biologists Vs Machine Learning Engineers

Battle Royale: Computational Biologists vs Machine Learning Engineers

From the first genome sequencing in the second revolution to Life Science Analytics as a growing field in the fourth industrial revolution, change has been both welcomed and fraught with fear. Everyone worries about robots, Artificial Intelligence, and in some cases even professionals who have stayed current by keeping up-to-date with trends. And it’s beginning to affect not only “office politics” within the tech space, but even interviewer and interviewee relationships. We’ve seen a growing trend of apprehension between Computational Biologists and Machine Learning Engineers. What could be the cause? Aren’t they each working toward a common goal? It seems the answer isn’t quite so cut and dry as we’d like it to be. Here are some thoughts on what could be driving this animosity. But first, a bit of background. So, What’s the Difference? Computational Biology and Machine Learning are two sides of the same coin; one sets the framework and the other applies what’s been learned. Both use statistical and computational methods to construct models from existing databases to create new Data. However, it is within the framework of biomedical problems as computational problems, that there seems to be a bit of a breakdown. It’s one thing to have all the information and all the Data, but its quite another to know how the Data might interact or affect the health and medications of people seeking help. This is the job of those in Life Science Analytics. Determine through Data what needs to be done, quickly, and efficiently, but at the same time, ensure the human element is still active.  A few examples of Computational Biology include concentrations, sequences, images and are used in such areas as Algorithmics, Robotics, and Machine Learning. The job of Machine Learning can help to classify spam emails, recognize human speech, and more. Here’s a good place to start if you’d like to take a deeper dive into the differences between the two or read this article about mindsets and misconceptions. Office Politics in the Tech Space Circling back to the concern between Computational Biologists and Data Scientists with a focus on Machine Learning. The latest around the water cooler within the tech space is that those with a biological background who understand Machine Learning are looked upon as dangerous to the status quo.  But, as many of our candidates know, it’s important to stay on the cutting edge and if that means, upskilling in Machine Learning so you have both the human element as well as the mathematical, robotic components, then that is more marketable than just having one or the other. The learning curve in biology training within the Life Sciences Analytics space means Computational Biologist with a Machine Learning skillset is best able to apply Data Science and computer science tools to more organic and biological datasets. Someone with just a computer science background may not have the depth of knowledge to understand how these models, systems, and data affect and impact medicine. Computational Biologists who are trained simultaneously in computer science and biology, and are a little heavier on the biology side, see Machine Learning Engineers as a threat because utilizing Machine Learning and other cutting-edge tools could mean their job is on the line. They worry their job will fall by the wayside. That when somebody proves Machine Learning is faster and more efficient the impetus might be why hire a Computational Biologist when a Machine Learning engineer will do? It’s like when a lot of people joke about how robots are going to take over the world and everybody will be out of a job. I think the worry with some folks on the Computational Biology side is that maybe they just aren’t up to date with their training or haven’t kept up with cutting edge of technology. With a Recruiter’s Eye While what I’ve seen agrees that, yes, Machine Learning is incredibly helpful and fast and you can get through so much more data. But its still that understanding of biology and chemistry that you will need because you need to be able to understand, for example, how these proteins are going to be reacting with one another or you need to understand how DNA and R&A work, how best to analyze, and what analyzing those things means. On the other hand, just because you know, “oh, this reaction comes out of it”, if you don’t know why that is or how that could impact a drug or a person, then you don’t really have anything to go on. There’s a caveat there. Though there may be concerns among Computational Biologists and Machine Learning Engineers, at both the upper and entry levels, it’s still the technical lead who will say, “we really do need somebody with a biological background because if we get all this Data and don’t really know what to do with it, then we’ll need to hire a Project Manager to converse between the two and that’s an inefficient use of time and resources”. What I hear most often is a company wants a Computational Biologist but they also want someone who knows Machine Learning. But they don’t want to compromise on either because they don’t understand there are limitations to things. We all want the unicorn employee, but we can’t make them fit into a box with too specific parameters. It’s a Fact of Life Any job, whether it’s in the tech industry, the food industry, Ad Optimization, or even recruitment, uses Machine Learning in one way or another. Yet compared to spaces which work on sequencing the human genome, it's amazing to see how far things have come. It used to take days to process DNA. Now you can spit in a tube and send it off to 23andMe to learn a little about your health. That’s what Machine Learning enables people to do. But it doesn’t mean Computational Biologists are going to fall by the wayside. It means there will be times you’ll have to liaise more between the two groups. It means you’ll be more marketable by adding Machine Learning to the work you’re already doing or taking some classes in Computational Science, for example, to keep your skills up to date. It’s a Transparency Issue Ultimately, it seems the heart of this apprehension comes down to a transparency issue. For example, let’s say companies begin to bring in AI people and suddenly the staff already in place begins to get worried about the security of their jobs. Even in an industry tense with skills gaps, the fear still abounds. In coming back to speak with the Hiring Manager, it became clear the animosity is even more prevalent than first imagined. So, it’s important to get input from within the company and develop a unified story, a unified message across departments, and especially within the Life Science Analytics and Data Science teams as well. In other words, “keep people in the loop.” If it’s happening to this company, it seems other companies may be facing this same issue. However, it’s not going away and is creating a kind of competition between the old guard and the up-and-coming startups. For example, any new company is going to want to integrate AI and will be asking the question how best to integrate it into their structure. They might also ask how best to optimize the ads coming through AI. This is just another way of how companies are catching up, but also how people are catching up to the companies.  Technology is coming whether you like it or not. So, if you want to stay marketable and work on really interesting projects, there’s always going to be the challenge of staying up-to-date and different companies attack this in different ways.  Stay open minded, keep an eye and an ear out for ways to stay on top of your game. Even just taking a few minutes to watch a YouTube video, listen to a TedTalk or a podcast, so you can talk about it and be informed. These are some really simple ways to stay on the cutting edge and help you figure out where you can grow and improve for better opportunities. Ready for the next step? Check out our current vacancies or contact one of our recruitment 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, call (212) 796 - 6070 or send an email to newyorkinfo@harnham.com.

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