Harnham
SEARCH
Shortlist

Clients

What We Do

Put simply, we deliver the most suitable and highly skilled professionals into your Data & Analytics team.

Whether it is Marketing & Insight, Risk Analytics, Data & Technology or Digital Analytics, for the team at Harnham it is key to fully explore and understand the career aspirations of our candidates. We do this whilst developing an in-depth knowledge of each marketplace and its emerging trends, as well as the different types of organisation that we work with and their diverse skill requirements. Only then, once we have the full picture, are we able to deliver resourcing solutions that ensure the very best outcome for all our customers.

HOW We Do IT

We offer our clients a complete recruitment solution across the breadth of Data & Analytics disciplines.

Our original business focus was within UK Data & Analytics but we have expanded to specialise in recruitment across a much wider variety of roles throughout the USA, along with the UK and Europe. Our continued focus on analytics means we gain valuable and current market knowledge along the way, ensuring we can offer you a truly specialist focus, which is second to none within our marketplace. We manage permanent and contract resourcing for all skills within Data & Analytics and, as members of APSCo, you are guaranteed a service based on excellence, best practice, quality, integrity and expertise.

What
sets us apart

We are here to make your recruitment process simple, easy and ultimately successful for everyone.

Our recruitment solutions are determined by tried and tested methods to ensure an effective solution for all concerned. Our focus on establishing networks of skilled individuals, as well as knowing our client businesses, culture and skill requirements guarantees we have a high success rate on our placements. 


Latest Jobs

Behavioral Data Scientist
Salary

US$70000 - US$135000 per annum

Location

District of Columbia

Description

An public health organization that uses AI to help vulnerable populations across the globe is looking for a behavioral scientist to join their team

ADD TO SHORTLIST
Head of Data Science
Salary

US$200000 - US$280000 per annum

Location

New York

Description

An innovative startup that just raised $150 million in series B funding is looking for a Head of Data Science.

ADD TO SHORTLIST
Fraud and Payments Manager
Salary

£75000 - £85000 per annum + Bonus + Benefits

Location

City of London, London

Description

We have a new position available with one of the biggest brands in the world when it comes to software companies. They are seeking a Fraud and Payments Manager

ADD TO SHORTLIST
Analytics Manager
Salary

£55000 - £60000 per annum

Location

Leicester, Leicestershire

Description

Are you an Analytics Manager who wants to work for a leading e-commerce company?

ADD TO SHORTLIST
Machine Learning Engineer
Salary

£400 - £450 per day

Location

City of London, London

Description

A chance to solve complex energy problems by building advanced Machine Learning Models in Python

ADD TO SHORTLIST
Digital Analyst
Salary

£30000 - £40000 per annum

Location

London

Description

One of the UK's most trusted brands seeks a technical digital analyst with SQL & BigQuery experience.

ADD TO SHORTLIST

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.

HOW AI AFFECTS US FROM JOURNALISM TO POLITICS

How AI Affects Us from Journalism to Politics

It’s been nearly 40 years since the War Games movie was released. Remember the computer voice, JOSHUA, who asked the infamous, “Would you like to play a game?”. The computer had been programmed to learn. You might call it a forerunner of Artificial Intelligence (AI) today. Except AI is no longer the little boy who becomes a stand-in for a grieving family. Now, we’re no longer watching a movie about AI, we’re living in its times. But unlike a movie, we won’t find a solution after 90-minutes to two hours. Now, we must be cautious and pay attention or we will be leapfrogged by our own inventions. Can we change course at this late stage? As we enter a new decade, let’s take a look at some of the concerns and solutions posed by Amy Webb, author of The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity.  How Did We Get Here? As Christmas approaches, we are cajoled by memories and makers to buy back our past and cement our futures with things. Our desires for instant gratification keep us from planning for AI properly. While it can be fun to watch AI play against Chess champions or worrisome to watch it direct our buying decisions, we remain secure in that its not yet to its full potential. But elements such as facial recognition and realistic generation cause concern for a number of reasons. Not the least of which is what will happen when systems make our choices for us. From the Big 5 of Tech to your local commercial or paper, our minds are already often made up. And even when we’re presented with the truth, we may not even realise it because our AI capabilities have grown exponentially and continue to grow making us wonder…what if? So, What Can We Do? Businesses, Universities, and the Media all have a part to play. And in our image-centric world, the greatest of these is Media. Universities can blend technical skills with soft skills and blend in degrees such as philosophy, cultural anthropology, and microeconomics just to name a few. The blending of these skills can offer a more robust understanding of the world around us.  Businesses can work to ensure a more diverse staff and improve inclusion. Shareholders and investors can help by slowing down when considering investments in AI to allow for determining risk and bias before moving forward. And when it comes to the Media, there’s general agreement the public needs greater media literacy. While AI-focused accusations of deepfakes in news and on television abound, there is a greater concern in that much of what people believe to be fake, isn’t. So, the question becomes, how does the media generate trust in a public that no longer believes what it  reads, sees, or hears?  It’s this casting of doubt which is the greater danger. Why? Because it requires no technology at all. While it’s best to be informed, it can be tricky to navigate in today’s world. So, it’s up to not only the news consumers, but is up to researchers, journalists, and platforms to separate the wheat from the chaff. Or in this case, the real from the fake before the news reaches its audience. From Socrates who taught his students to question what they learned to the students of the 20th century expected to remember only what was needed for a test; we have come full circle. But at a unique time in our world, in which the questioning has not much to do with challenging ourselves but is at best used to sow distrust.  While tech companies like Facebook and Google have jumped on the bandwagon to expose fakes, others are moving into how to build trust. Again. At best, these startups offer comparisons of videos and images as the human eye works to discern the difference.  But while tech may be advancing technological wonders by leaps and bounds, there remains a solid grounding of the human element. Humans are needed as content moderators to dispel fiction from truth. And in the media? There’s a renewed focus on training journalists to fact check, detect, and verify their stories. The human element adds a layer of nuance machines can’t yet emulate. If you’re interested in AI, Big Data and Digital or Web Analytics, we may have a role for you. Take a look at our current opportunities, or get in touch with one of our expert consultants to find out more. 

Sean Alunan

Sean Alunan

19. December 2019

How to Succeed in Self-Service BI

How to Succeed in Self-Service BI

Business Intelligence, along with Business Analytics and Big Data, is one of the terms often associated with decision-making processes in organisations.  However, there is little discussion around the importance of what skills decision makers in your organisation need to use the technology efficiently.  In recent years, the development of user-friendly tools for BI processes, Self-Service BI are increasing. Self-Service BI is an approach to BI where anyone in an organisation can collect and organise data for analysis without the assistance of data specialists. As a result of this, many businesses have invested in comprehensive storage and information processing tools. However, many are beginning to find that they are not able to realise the gains of these investments as they were expecting, may often due to underestimating the difficulties of introducing these systems into the current processes and transforming existing knowledge into actual actions and decisions.  In a worst-case scenario, if left unplanned, Self Service BI can sabotage your successful BI deployment by cutting mass user adoption, impairing query performance, failing to reduce report backlogs, and increasing confusion over the “single truth”. To prevent this from happening, here are our top three tips for ensuring the right implementation of SSBI in your company: UNDERSTAND YOUR USERS’ NEEDS There are three major user areas for analytics tools: strategic, tactical and operational. The strategic users make few, but important decisions. The tactical users make many decisions during a week and need updated information daily. Operational users are often closest to the customer, and this group needs data in its own applications in order to carry out a large number of requests and transactions.  Understanding the different needs of each group is necessary to know what information should be available at each given frequency to help scale the BI solution.  HARNESS THE POWER OF ADVANCED USERS To ensure a successful BI deployment, utilising advanced users is key. Self-service BI is not a one-size fits all approach. Casual users usually don’t have the time to learn the tool and will often reach out to ‘Power Users’ to create what they need. Hence, these users can become the go-to resource for creating ad-hoc views of data. Power Users are the ideal advocates for your business’ self-service BI implementation and should be able to help spur user adoption.  UPGRADE INTERNAL COMPETENCIES  Our final tip for a successful implementation is to communicate the new tool thoroughly to the users.  It is highly unlikely that employees who have not been involved in the actual development project will immediately understand what the tool should be used for, who needs it, and what it should replace. By upgrading internal competencies, you can avoid becoming dependent on external assistance. Establishing a cross-organizational BI competence centre of 5-10 members, who meet regularly to share their experiences will help drives and prioritise future use of the tool. The added benefit of a successful implementation is that it will generate new ideas from users for how the organisation can use data to make better decisions. If you have the skillset to implement Business Intelligence solutions, we may have a role for you.  Take a look at our latest opportunities or get in contact with our team. 

Elise Myhren

Elise Myhren

08. October 2018

Recently Viewed jobs