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Site Terms

Access to and use of the Harnham website is subject to the following terms and conditions.

Copyright

Copyright ©  Harnham 2013. All rights reserved. All copy and other intellectual property rights in all text, images, sounds, software and other materials on this site are owned by Harnham, or are included with permission of the relevant owner.

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Contents

The information on this site has been included in good faith but is for general informational purposes only. It should not be relied on for any specific purpose and no representation or warranty is given as regards its accuracy, completeness or fitness for any particular purpose. Save to the extent that such limitation is not permitted under English Law Harnham, nor any of it's employees shall be liable for any loss, damage or expense arising in contract, tort or otherwise out of any reliance on information contained in this site, access to or use of or inability to use this site or any site linked to it including, without limitation, any loss of profit, indirect, incidental or consequential loss.

Use

Your information and activity on this site must not:

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This site is intended normally to be available 24 hours a day 7 days a week.
You agree to fully reimburse Harnham in respect of all losses, costs, actions, claims, and liabilities incurred by Harnham as a result of any breach or non-observance by you of these terms or any data submitted by you to us.

Harnham will make all reasonable attempts to exclude viruses (and similar destructive devices) from the site but cannot guarantee the exclusion of viruses (and similar destructive devices), and you should take appropriate steps in respect of this risk.

Linked sites

At various points throughout the site, you may be offered automatic links to other internet sites relevant to a particular aspect of this site. This does not indicate that Harnham are necessarily associated with any of these other sites or their owners. While it is the intention of Harnham that you should find these other sites of interest, neither Harnham nor their employees shall have any responsibility or liability of any nature for these other sites or information contained in them.

These terms shall be governed by and construed in accordance with English Law and each party to these terms submits to the exclusive jurisdiction of the English Courts.

Company Registration Number: 05723485. Registered Address: 1st Floor, Ashville House, 131-139 The Broadway, Wimbledon, London, SW19 1QJ. Registered by Companies House, Cardiff.



Cookie Policy

If you are uncertain about what a cookie is have a look at our simple guide to find out how we use them on our website.

What is a cookie?

Cookies are text files containing small amounts of information which are downloaded to your device when you visit a website. Cookies are then sent back to the originating website on each subsequent visit, or to another website that recognizes that cookie.

Cookies do lots of different jobs, like letting you navigate between pages efficiently remembering your preferences, and generally improve your web site experience. They can also help to ensure that adverts you see online are more relevant to you and your interests.

We can split cookies into 4 main categories:

  • Category 1: strictly necessary cookies
  • Category 2: performance cookies
  • Category 3: functionality cookies
  • Category 4: targeting cookies or advertising cookies

Category 1 - Strictly necessary cookies

These cookies are essential in order to enable you to move around the website and use its features,
such as accessing secure areas of the website. Without these cookies services you have asked for,
like register for job alerts, cannot be provided.

Please be aware our site uses this type of cookie

Category 2 - Performance cookies

These cookies collect information about how visitors use a website, for instance which pages visitors go to most often, and if they get error messages from web pages. These cookies don’t collect information that identifies a visitor. All information these cookies collect is aggregated and therefore anonymous. It is only used to improve how a website works.

By using our website and online services, you agree that we can place these types of cookies on your device.

Category 3 - Functionality cookies

These cookies allow the website to remember choices you make (such as your user name and password) and provide enhanced, more personal features. These cookies can also be used to remember changes you have made to text size, fonts and other parts of web pages that you can customize. They may also be used to provide services you have asked for such as watching a video or commenting on a blog. The information these cookies collect may be anonymous and they cannot track your browsing activity on other websites.

By using our website and online services, you agree that we can place these types of cookies on your device.

Category 4 - targeting cookies or advertising cookies

These cookies are used to deliver adverts more relevant to you and your interests. They are also used to limit the number of times you see an advertisement as well as help measure the effectiveness of the advertising campaign. They remember that you have visited a website and this information is shared with other organizations such as advertisers. Quite often targeting or advertising cookies will be linked to site functionality provided by the other organizations.

We do have links to other web sites and once you access another site through a link that we have provided it is the responsibility of that site to provide information as to how they use cookies on the respective site.

You can find more information about cookies by visiting www.allaboutcookies.org or
www.youronlinechoices.eu.



Privacy Policy

Harnham places great importance on trust and confidence in our measures to protect your privacy. This page will let you know what information is collected by us and what it is used for.

Your name, address, telephone number and email address is collected by us along with your CV and application data.

Once relevant information has been supplied concerning your application, Harnham will use this information to:
  • Locate suitable employment. Candidates are requested to instruct Harnham on application if they wish for any details to be restricted from any parties or companies they do not wish to Harnham to approach on their behalf.
  • Harnham may keep you informed of job opportunities and contract assignments which we think may be of interest to you
  • Harnham may email you periodically with relevant news and offers (but not from 3rd parties) that complement our efforts to find suitable job opportunities for you

Information Collection and Use

Harnham  is the sole owner of the information collected on this site. We will not sell, share, or rent this information to others. Harnham collects information from our users at several different points on our website.

Registration

We request information from the user on our online registration forms. Here a user must provide contact information and information regarding the type of work you are seeking and your skills, qualifications and experience. This information is used to enable us to provide you with work-finding services. If we have trouble processing your application, this contact information is used to get in touch with you. Harnham does not use this information for any other purpose.

Security Measures

All data stored at Harnham is held in a fully protected environment. We ensure that any data held by us is monitored internally against unauthorized access, destruction, loss or manipulation. Our systems and IT staff remain constantly vigilant to protect the sensitive information we retain.

Correction/Updating Personal Information:

If your personally identifiable information changes (such as office address), we will endeavor to provide a way to correct, update or remove the personal data provided to us. This can usually be done by contacting us directly.

Notification of Changes

If we decide to change our privacy policy, we will post those changes on this page so our users are always aware of what information we collect, how we use it, and under circumstances, if any, we disclose it. If at any point we decide to use personally identifiable information in a manner different from that stated at the time it was collected, we will notify users by way of an email. Users will have a choice as to whether or not we use their information in this different manner. We will use information in accordance with the privacy policy under which the information was collected.

Data retention policy

We will hold your personal data on our systems for as long as is reasonably necessary, and when this information is no longer needed we will securely delete such data. On request, we will provide information in writing about your information stored on our database. If you do not wish us to directly market to you, by phone, email, SMS etc. you may notify us of this in writing. We will then suppress the personal information we hold about you on our database and ensure that your wishes are carried out. Requests to delete personal data will be considered but actioned in accordance with any overriding data protection policy and / or other legal requirements.

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

How to lead a Data team

How To Lead A Data Team

Dream teams from sports to business are an ideal everyone aspires to live up to. But what is it every basketball or football dynasty has which makes them a dream team? What is it that brings individuals together to overcome odds, set examples, find solutions, and create the next best thing? Good management.  The need for good management is no different in the Data Science world. Yet according to our latest Salary Guide, poor management is one of the top five reasons Data professionals leave companies. So, let’s take a look at what poor management is, what causes it, and how businesses can better retain Data talent. What’s Your Data Science Strategy? Most businesses know they need a Data team. They may also assume that a Data Scientist who performed well can lead a Data team. But that isn’t necessarily the case. Managers have to know things like P&L statements, how to build a business case, make market assessments, and how to deal with people. And that’s just for a start.  The leader of a Data team has a number of other factors to consider as well such as Data Governance, MDM, compliance, legal issues around the use of algorithms, and the list goes on. At the same time, they also need to be managing their team with trust, authenticity, and candor. The list of responsibilities can be daunting and if someone is given too much too soon and without support, it can be a recipe for disaster. Other businesses might believe that a top performing Data Scientist would make a good manager. Yet these are two different fields. Or you might look at it this way. If you are willing to upskill a top performing Data professional and train them in managerial skills, giving them the education and support they need, that is one solution. Another solution is to create a Data Science strategy which brings in people with business backgrounds. Data Science is a diverse field and people come from a number of backgrounds not just Computer Science or Biostatistics, for example.  Now that you’ve seen what might cause a manager to fail, let’s take a look at a few tips to help you succeed. Seven Tips for Managing a Data Team Managing a team is about being able to hire, retain, and develop great talent. But if the manager has no management training, well, that’s how things tend to fall apart. Here a few tips to consider to help ensure you and your team work together to become the dream team of your organization: Build trust by caring about your team. Help define their role within the organization. Ensure projects are exciting and that they’re not being asked to do project with vague guidelines or unrealistic timeframes.Be open and candid. Remember, Data Scientists are trained in how to gather, collect, and analyze information. If anyone can see right through a façade, it will be these Data professionals. Have those “tough” conversations throughout every stage of the hiring, onboarding, and day-to-day, so that no one is caught unaware.Offer consistent feedback. And ask for it for yourself as well from your team.Ensure your team understands the business goals behind their projects. Let them in on the bigger picture. Think long-term recruitment for a permanent role, not short-term. If you have an urgent project, consider contracting it out. Prioritize diversity to include academic discipline and professional experience. Does the way this person view the world expand the knowledge of your team’s knowledge? Dream teams don’t always have to agree. Sometimes, the best solutions are found when there are other opinions. Finding the perfect, “Full Stack” Data Scientist or Data Engineer or Analyst is not impossible, and retaining them can be even easier. If you’ve done your job well, your team will trust you, have a balanced skillset, and understand how their work supports the organization and its goals. For more information on how to be a great manager, check out this article from HBR.  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.

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.

Data Engineers: The Workers Behind the Curtain

We’re halfway through the year and our salary guide is out. If you wonder where you are, where you’re going, and if you’re a business, how you’re going to get there. Well, then, you’ve come to the right place. Articles have touted Data Scientists as the “rock stars” of the 21st century, but even rock stars need their managers and roadies. Who else will build the stage and plan the tour? And in the world of data, it all begins with the Data Engineer, laying the groundwork, the foundation, and the framework. These are the stars behind the scenes who make it possible for Data and Data Scientists to be front and center. Send a Data Engineer Over As prevalent as Data has become in our lives and as its importance grows, there remains the challenge of Data Management. If you don’t know why something is built or how to navigate the structure, the Data you do receive may not make much sense. Your guide in this journey is the Data Engineer, one of the most important pieces of your Data Management puzzle.  These highly skilled and sought-after professionals should not be confused with a Software Engineer, though some elements may be transferable between the two. The building blocks to put massive amounts of Data into a scalable system both reliable and secure takes a unique set of skills.  Humans at the Helm as Skills Shift  As much as we depend on Data today to help determine actionable insights for our business and as much as we hear about the rise of machines in the form of Artificial Intelligence, Machine Learning, and Deep Learning, it is ultimately humans who are at the helm.  It is the people behind the curtain of Data who will build it, run it, and make it work. It is also people who are typically the biggest costs in a project. Finding the balance and ideal candidate, the right person with the right skills for the job, is critical to success. And if you’re starting from the ground up, Data Engineers who can work with the core tools of databases and Spark, for example, will see their opportunities grow.  In our Salary Guide for 2019, we learned one of the skills most sought after by companies today is knowing AWS/Azure and moving Data Lakes into the Cloud. Small businesses and startups are moving to the Cloud to help them scale their Data, but someone still needs to lay the groundwork, whether it’s for the small business or the public cloud providers. Data Engineers are in high demand and it doesn’t look as though things will be slowing down anytime soon. The field is slick with potential. The Time Has Come for Transparency Data is binary gold and, with enough of it, you can read or estimate the mind of your customer or you can wreak havoc on someone’s life. Just a year ago, the European Union put into place rules and regulations as well as financial consequences for poor Data Governance under the General Data and Protections Regulation Act (GDPR). Though the U.S. doesn’t yet have a similar law, there are still plenty of mandates to be aware of by states, unions, and countries.  One Final Thought As roles and technology evolves, it’s important for businesses, employees, and stakeholders to evolve as well. Whether that means making sure to implement practices for Data transparency or upskilling and reskilling your workforce to keep up or simply knowing the trends of forward-thinking companies to scale your own business. Data fuels digital innovation and organizations who are prepared to find solutions will benefit. Want to know what else is trending in big data? Here are a few trends in Big Data forward-looking organizations should look out for in this year and toward the next. 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 & 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.

A Data Engineer is a Unique Blend of Data Professional

From startup and small business to large enterprises, each type of business requires a unique blend of Data professional. Though in today’s world, much of the Data being gathered, catalogued, and analyzed happens both in the Cloud and on a hard drive, each type of business has a different need, budget, goals, and objectives. But there is one thing each and every business will have in common. At the heart of the Data team will be a Data Engineer. The Three Main Roles of a Data Engineer This is an analytics role in high demand. It is a growing and lucrative field with steps and stages for nearly every level of business and education experience. For example, a Data Scientist interested in stepping into a Data Engineer role might begin as a Generalist. In all, there are three main roles for each level and type of business – Generalist, Pipeline-Centric, and Data-Centric. Let’s take a quick look at each of the roles with an eye toward the type of person who might be the best fit: Generalist – Most often found on a small team, this type of Data Engineer is most likely the only Data-focused person in the company. They may have to do everything from build the system to analyze it, and while it carries its own unique set of skills, it doesn’t require heavy architecture knowledge as smaller companies may not yet be focusing on scale. In a nutshell, this might be a good entry point for a Data Scientist interested in upskilling and reskilling themselves to transition into a Data Engineering role.Pipeline-centric – This focus requires more in-depth knowledge working with more complex Data science needs. This type of role is found more often in mid-sized companies as they grow and incorporate a team of Data professionals to help analyze and offer actionable insight for the business. In a nutshell, this role creates a useful format for analysts to gather, collect, and analyze each bit of Data at each stage of development.Database-centric – This role is found most often in larger companies and deals not only with Data warehouses, but is focused on setting up analytics databases. Though there are some elements of the pipeline, this is more fine-tuned. In a nutshell, this role deals with many analysts across a wide distribution of databases. A Fine Balance Between Technical Skills, Soft Skills, and Business Acumen While it’s important for anyone filing this role to have deep knowledge of database design as well as a variety of programming languages, its equally important to understand company objectives. In other words, once the groundwork is laid and the datasets established, it’ll be important to explain what it is the business executives need to know to make the best decisions for their business.  Knowing how and what to communicate to executives, stakeholders, and your Data team also means understanding how to best retrieve and optimize the information for reporting. Depending on your organization’s size, you may need both a Data Analyst or Scientist and a Data Engineer. Though this is less likely in medium and larger enterprises. On the flip side, in order to understand the business’ needs, you’ll also need to be good at creating reliable pipelines, architecting systems and Data stores, and collaborating with your Data Science team to build the right solutions. Each of these skills are meant to help you understand concepts to build real-world systems no matter the size of your business. One Final Thought… Do you like to build things? Tweak systems? Take things apart and see how they work, then put them back together better and more efficient than before? Then Data Engineering might be for you. 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.

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