Harnham

Biostatistics jobs

What We Do

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

Despite the broad range of Biostatician roles available, they continue to play a crucial role in post-clinical trials. Working closely with clinical teams, they bring the statistics behind the data to life.

With roles across a variety of verticals available, their statistical insights provide new ways of looking at a range of data; from general healthcare, to individual cases.

how We Do it

Our specialist Biostatistics team’s unique understanding ensures exceptional service throughout the entirety of your job search or staffing process.

We have the knowledge, the network and the required drive to find the best candidates on the market, as well as working with some of the most exciting Life Science businesses around.

If you’re hoping to change careers or are looking for the right talent to fill an opening, Harnham can help.

Latest Jobs

Biostatisician
Salary

US$100000 - US$130000 per year + BENEFITS

Location

San Francisco, California

Description

Change the industry of neurodegenerative diseases and drug discovery

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Senior Biostatistician
Salary

US$125000 - US$150000 per year + BENEFITS

Location

Pleasanton, California

Description

Have a passion for biostatistics? Apply now!

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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.

AR & VR Breathe Life Back Into Our Lives

AR & VR Breathe Life Back Into Our Lives

Remember the bicycles piled in the yard that showed where your friends were? What about the jingle of coins in your pocket as you headed to the arcade? Stranger Things may have recalled these distant memories, but what if you could still see bicycles piled against your neighbors’ door or listen to the jingle of coins as you played with your friends? This is Augmented Reality and its aim now is to get you off the couch, exercising, playing, and enjoying camaraderie. Ready, Player One? Five Trends to Watch As we navigate the next stage of our virtual and augmented realities, there are a few trends to watch. AR, VR, and AI Will “See” Objects - Augmented Reality (AR), combined with Artificial Intelligence (AI) and Computer Vision, will help computers “see” and label what’s being seen. Machine Learning will ramp up to offer increasingly correct identification of objects whether it’s the dinosaur exhibit at the natural history museum or connects the dots for stargazing in a planetarium.VR Gets More “Real” for the Mainstream – In other words, developers are able to offer more immersive experiences. New developments in hardware technology, such as eyeball tracking and field-of-view help power the idea users can interact and explore less like a video game and more like real-life.AR Can Help Keep Your Eyes on the Road – Remember KIT? The car who talked, could self-diagnose, and navigated with barely a hand on the wheel? It’s not so far-fetched now as it once seemed as vehicle manufacturers increasingly opt for voice assistants and some begin to offer graphics’ overlay of footage around the car. Others go a step farther, projecting data onto the car windshield, assisting with navigation, lane identification, and potential hazards along the way.AR-Based Entertainment Branches Out – No more piled high pizza boxes, sitting in the dark of your parent’s basement. AR today is about getting moving; physical activity and balancing tech life with real life. Toys and Gaming companies are on the bandwagon to get families moving. Location-based gaming has grown by leaps and bounds as has interactive projection-based technology. Some applications can transform your immediate environment into an immersive gaming experience while others can transform playgrounds which, when unlocked by parents, can offer choose-your-own adventure types of projects to complete. Enter whole being of mind, body, spirit. And we’ve barely scratched the surface.Worldbuilding, Personalized Character Building, and Augmented Board Games – Each of these are about bridging the gap between the physical and digital world and is most changed when it comes to board games.  As exciting as these trends are, it’s not all fun and games when it comes to the next advances of AR. This technology is also being used to help discover early onset of Alzheimer’s and most recently has found its way into the operating room. Or at least, it will be soon as companies look to bring the AR and VR technologies into the OR. Training and Teaching with AR AR & VR technologies are being used for teaching and training in just about every industry it seems. From Walmart to the Military, business is seeing the benefits of allowing individuals to practice their roles without the associated real-world risks. But when it comes to the healthcare industry, this is where AR begins to really shine. What if we could predict not only detect early onset dementia, but catch the onset of mental illness as well? One company, recently cleared by the FDA, is working toward just that, with the specific goal of predicting Alzheimer’s early. With an estimated cost of around $290 billion which could rise to over $1 Trillion by 2050, their claims of 94% accuracy in detection 6 to 10 years early is good news for families. Memories are how we share our stories and no family wants to miss theirs. Could technology as disparate as it once made us be bringing us closer together? With these latest, that just may be the case. So, whether you want to let out your inner child, practice a new skill without real-world ramifications, or simply know your memories will be with you for a lifetime, AR offers something for everyone. Every industry. Every business. It has infused our world and is breathing life back into our lives.  Want to be the wizard behind the curtain, the Data Analyst to know what’s next, or the Data Engineer who builds the next great technological advance in the AR spectrum of services and capabilities? We may have a role for you. 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.

Mairead Holt

Mairead Holt

08. August 2019

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.

Alyssa Liew

Alyssa Liew

04. July 2019

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