Harnham

How Algorithms Shape Our World



Kevin Slavin argues that we're living in a world designed for -- and increasingly controlled by -- algorithms. In this riveting talk from TEDGlobal, he shows how these complex computer programs determine: espionage tactics, stock prices, movie scripts, and architecture. And he warns that we are writing code we can't understand, with implications we can't control.

Watch this 15 minute video (which has divided opinion based on the feedback) to learn more...





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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.

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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.

Thomas Daughtrey

Thomas Daughtrey

11. June 2019

The Harnham 2019 Data & Analytics Salary Guide Has Arrived

We are thrilled to announce the launch of our 2019 Data & Analytics Salary Guide. With over 1,500 respondents across the USA, this year’s guide is our largest and most insightful yet.  Looking at your responses, it is overwhelmingly clear that the Data & Analytics industry is continuing to thrive. This has led to an incredibly active market with 72% in the US willing to leave their role for the right opportunity.  Salary expectations remain high, although we’re seeing that candidates, on average, expect 10% more than they actually achieve when moving between roles.  We’ve also seen a change in the reasons people give for leaving a position, with a lack of career progression overtaking an uncompetitive salary as the main reason for seeking a change.   There also remains plenty of room for industry improvement when looking at gender parity; the US market is only 23% female, falling to 17% in Data Engineering roles and 16% in the Data Science space.  In addition to our findings, the guide also include insights into a variety of markets and recommendations for both those hiring, and those seeking a new role.  You can download your copy of the guide here.

Stephanie Brooks

Stephanie Brooks

10. June 2019

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.

Riley Hsia

Riley Hsia

05. June 2019

Common Mistakes About Data Science And Your Role Within It

Earlier this month I had the pleasure of speaking at ODSC East, as the best future talent Data Science talent gathered together to discuss the direction of our industry.  With Data Science becoming such a broad term that covers a number of functions, and with the rise of new areas such as Blockchain, AI and ML, I wanted to talk about what it actually means to be a Data Scientist now, and in the future.  With this in mind, we conducted a survey over the course of the event where we asked what Data Science meant to the people there. Here’s what we found out: WHAT IS DATA SCIENTIST, ACTUALLY? Every company thinks they need one, and every analyst wants to be one, but more and more job titles that are not necessarily Data Science are now being billed as Data Scientists. In fact, when we asked people what they considered their job title to be, regardless of experience, Data Science came out on top: Data Scientist: 58% Data Analyst: 22% Machine Learning Engineer: 10% Business Intelligence Analyst: 9%  However, from my experience, this is not necessarily accurate. I once worked with the Senior Manager of Data Science in a very well established Retailer. He’d been there for less than one year and was already on the job market. In his interview he had been told that the company were fully behind investing in a top-class Data Science department but had actually ended up managing a team of people who were building dashboards creating reports for all areas of the business. This is much less Data Science, and much more Business Intelligence.  This confusion is quite typical within the industry and frequently needs to both unhappy employers and employees.  MORE THAN JUST TOOLS One common mistake when it comes to misidentifying Data Scientists is a result of people focusing on the tools people use. Whilst both Data Scientists and Marketing & Insight specialists might be skilled up in Python, R and SQL, their methodologies are significantly different. When asked to define a true Data Scientist at the event, 73% of people agreed the definition is: “A person who uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data.” Companies who panic about needing a Data Scientist to keep up with their competitors often ignore these crucial points and end up listing  every tool on a job spec. Frequently those who claim they want a Data Scientist actually want an Insight Analyst who can understand how customers behave, what they respond well to, what they’re talking about on social media, and how this unstructured data can be used to help their business make better decisions. WHAT DOES THIS MEAN FOR ME? For someone wanting to work in the Data & Analytics field there is one key rule: Know Yourself.  Think carefully about aspects within your Science, Operational Research, Statistics, and Analytics in general that you enjoy and how you can work them into your career. If you’re in college and just starting your career, don’t limit yourself by the sectors you think you have to work in; enjoy gaming? The gaming industry uses Data to make characters more lifelike, make sure they move in real-time and ensure that they play in a realistic way.  Just as crucial, however, is having an understanding of what the analytical teams around you do. Consider what roles they play in your business and how you are all interlinked, whilst being aware of the unique differences between roles. And, outside of analytics, those who understand what impact their work has on a business will always stand out amongst a crowd.  Essentially, don’t let yourself be limited by the title of Data Scientist. There are hundreds of roles within Data & Analytics so think about which one is right for you, rather than following the crowd.  If you’re looking for your next opportunity in Data & Analytics, or are looking to build out a team, take a look at our latest roles or get in touch with one of our expert consultants: 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.  Or, if you'd like to talk to me directly about anything I've talked about above, feel free to drop me a line at jennikavanagh@harnham.com.

Jenni Kavanagh

Jenni Kavanagh

30. May 2019

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