SEO Jobs

 

At Harnham, one of our key aims is to stand out from our competitors in as many ways as possible. We feel confident that we achieve this aim in various ways; our delivery, industry expertise and knowledge, to name a few.

However, In a rapidly evolving marketplace, where organisations are striving to rank as highly as possible in organic searches, we also recognise the importance of SEO and the value your skills can add to any business.

If you wish to work with an organisation who will partner with you to help optimise your job search and rank the best opportunities for you, please get in touch.



Latest Jobs

Salary

€36000 - €45000 per annum

Location

Paris, Île-de-France

Description

En tant que Consultant SEO, vous interviendrez dans la gestion de projets grands comptes.

Salary

€40000 - €45000 per annum

Location

Lyon, Rhône-Alpes

Description

Poste de Chef de Projet SEO Senior au sein d'une agence lyonnaise spécialisée SEO avec une typologie de clients parisiens.

Salary

€40000 - €45000 per annum

Location

Lyon, Rhône-Alpes

Description

Super opportunité pour un expert SEO en quête de projets d'envergure.

Salary

450000kr - 600000kr per annum + BENEFITS

Location

Oslo

Description

Et digitalt fokusert medie hus søker en SEO spesialist som kan være ansvarlig for søkemotoroptimalisering

Salary

£30000 - £40000 per annum

Location

London

Description

Work for a well-established and respected travel & tourism brand as their designated SEO specialist

Salary

£38000 - £40000 per annum

Location

London

Description

A great opportunity to take on an SEO management position at this global travel and tourism company.

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 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. 

Will Artificial Intelligence Revolutionise Eye Healthcare?

Faced with a rapidly expanding and increasingly older population, Healthcare resources in both the UK and US are facing an unprecedented level of demand. With only limited resource available, conversation is beginning to turn to the potential use of Artificial Intelligence (AI) to ease some of the strain. A recent example already seeing success is the current collaboration between Google’s DeepMind and London’s Moorfields Eye Hospital. But, as the lines begin to blur between human and machine-diagnosis, it’s worth questioning what role AI should actually play.  SEEING THE POTENTIAL IN AI Aside from the increase in population, there are many societal elements that are affecting the healthcare system. An increase in illnesses such as diabetes has led to a rise in eye-diseases and increased demand on optometrists.  Fortunately, AI can speed up the process with new technologies allowing systems like DeepMind to make their own diagnosis. Optical Coherence Technology (OCT) allows optometrists to create a 3D scans of people’s eyes. By bouncing near-infrared light of the interior surfaces of the eye, it can create an image that will reveal any abnormalities. DeepMind has been trained on over 15,000 scans and can now form a likely diagnosis, having used algorithms to find common patterns within the data.  Head of DeepMind, Mustafa Suleyman, says: “ [This could] transform the diagnosis, treatment, and management of patients with sight threatening eye conditions [...] around the world.” However, with an accuracy of just over 94%, there is still enough room for error to cause concern, especially given the potential consequences of an incorrect diagnosis.  LOOKING FOR MISTAKES  This doesn’t mean we should rule out the use of AI altogether. Whilst we may not be able to solely rely on the technology for diagnosis, it can be effective when working hand-in-hand with a human skillset.  In particular, by using AI systems for Triage purposes (determining what order patients should be seen in), as opposed to making a full diagnosis, patients demonstrating more significant symptoms could be reported and seen by a medical professional as priority, potentially leading to a higher chance of recovery.  When AI is used as a driver for patient management, as opposed to being viewed as alternative physician, it can create a faster and more efficient process.  To help continue to improve the results produced by DeepMind, the NHS have been given a validated version to use for free for the next five years. Using real-world applications over this time should streamline both their processes, and the technology itself.  A LONG TERM VISION For the time being, AI’s role within Eye Health is one of evolution, not revolution. With the inconsistency of current technology and the impact of incorrect results on people’s sight, it can only be utilised as a supporting tool.  For now, the skillsets of Data Analysts and medical doctors remain too separate to full work hand-in-hand. Add to this the risks of automation bias (a willingness to blindly trust a machine’s output), and the margin of error is too high.  However, that’s not to say that AI can’t and won’t play a significant part in the future of Healthcare. With the technology to detect eye conditions through the lens of your smartphone camera closer than ever to mainstream use, AI is set to play a huge role in outpatient treatment. At this stage, however, that role will be one of risk predictor, not eliminator.  If you think you have the skillset to help take AI to the next level in Healthcare we may have a role for you. Take a look at our latest opportunities or get in contact with our team. 

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