Harnham

Testimonials



CANDIDATES


Credit Risk Manager

"My experience with Harnham was very positive. Although I was new to the UK, they studied my CV and understood my background, so very quickly they were able to find roles that suited my previous experience. They helped me prepare thoroughly for all of my interviews and gave me prompt and clear interview feedback from their clients.

Throughout the process they also helped me when it came to managing my own expectations. I would sincerely recommend Harnham to my friends and colleagues and I will not hesitate to contact them in the future if I think about changing jobs again."


Business Intelligence Consultant

"I was approached by Harnham who quickly contacted prospective companies on my behalf. It was clear when I worked with them that they were well respected amongst their clients and this reflected well on my CV. Harnham kept in regular contact and provided useful feedback on the interviews I had. I have already recommended them to friends in the industry."


SAS Programmer

"My experience with Harnham was everything a candidate should expect from a recruitment company. They are the only agency that I would have no hesitation in recommending." 

CLIENTS


HR Director – Major Blue chip pharmaceutical company

"We have developed an excellent working relationship with Harnham. They understand the needs of our business and consistently deliver a high quality service. Harnham adopt a professional and honest approach with regards to the candidates they put forward, and they give excellent feedback on the market conditions which enables us to remain a competitive and attractive employer." 


Global Sourcing Manager – Internet company

“We have worked with Harnham for three years now, sourcing candidates for business critical analytics roles. They are a skilled, professional and dedicated team and the ease with which Harnham consultants interpret our requirements and match them to high-calibre professionals means we have consistently been able to capture the best people in the market. Harnham is always our first point of call for ensuring successful analytical placements.” 


ND – Head of Credit Risk

"The most important aspects of an agency relationship for us are delivery and professionalism. We have found Harnham to score very highly on both of these as well as providing helpful honest feedback on the state of the market and their candidates capabilities." 


Head of Customer Analytics – International Retail Bank 

“Harnham has assisted us over the past 10 months to help expand our customer analytics function. They are a professional, committed and knowledgeable team who have provided high quality candidates and have understood our requirements thoroughly. They have consistently delivered high-calibre professionals for our team and will be an ongoing source for analytical placements.”

GLASSDOOR REVIEWS


Explore the reviews from our happy candidates, clients and staff on Harnham's Glassdoor page.

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.

Creating Your Own ‘Unicorn’ Employee

The elusive unicorn. Once a mythical beast, it is now a term for a new mythical creature; the unicorn employee. As Data fields transition from generalist to more specialised niches within the industry, businesses are realising the need for more agile and adaptable employees. However, there is a bit of a twist on the business end. It’s a mix of a diversified skillset and expertise. Though one seems at odds with the other, it doesn’t have to be. On the flip side, employees want development, citing it as the number one reason for leaving a business in our 2019 Salary Guide. So, we thought we’d take a look and see where the disconnect was. After all, if employees want development and businesses want diversification, couldn’t the two come together for the benefit of all?  In a word, yes. Investment in employees through reskilling and upskilling are two important and useful ways to create your ideal employee and placement. There’s no better return on investment. Let’s take a look at how finding your unicorn employee can add value to your business. Think Outside The Job Description While the job description offers a good guideline of what’s expected in your day-to-day role, it can’t predict the changes, trends, and other issues within your industry. And in the digital tech world, change is the name of the game. Businesses need someone who can react quickly and effectively. Employees need to have skills either to manage the job themselves or know when to reach out to team members for help. This can’t happen in a siloed situation.  A few traits of the unicorn employee include flexibility, a curious nature, excited about learning new things, and the openness to offer suggestions within and across teams.  In a recent LinkedIn article, Hootsuite CEO Ryan Holmes captured it best. “Like actual unicorns, they’re hard to find, but once hired, offer up enormous benefits in the workplace. To name a few, they shatter expectations, raise the bar for everyone and are simply a joy to be around. Unicorn employees can literally take your business to the next level.” If you’re looking to hire a unicorn employee, look beyond their resume. While it’s a tool and will offer skills the employee has now, it can’t show you whether or not he or she will go the extra mile. And like the mythical beasts, these unicorn employees may come from surprising places, be open to new possibilities and think beyond the job description.  How to become a Unicorn Employee Be Coachable. Have a growth mind-set, a desire to learn, and find every opportunity to upskill. This is lifelong learning at its finest.Be a hard worker, but know when to rest and recharge.Raise the bar as a teammate and encourage others to do the same. Raise your Emotional Intelligence. Demonstrate empathy, be aware of your emotions and your teammates’, and help motivate others. How to Attract and Retain Top Talent As you plan your next level of hire in search of the not-so-elusive ‘unicorn’ employee, consider these few steps to get you on the right track. Understand job roles. The job beyond what’s on paper. See what it’s like on the other side and make assessments from the point of an employee. What’s their day-to-day routine, touchpoints, and technology turn-ons to help them do their job?Employee experience and technology are forever entwined. What tech skills do your potential employees have and what would they like to learn? Does their curiosity spark yours? Broaden your range. Encourage employee participation in technology decisions and include people from a wide range of levels and departments. Let them help with planning, selection, and design. After all, who better than those who use it and know it inside and out?To upskill is to create lifelong learning opportunities through classes and beyond. Other ways to upskill include exploring new mind-sets, developing diverse relationships, and redefining how people work. These few suggestions scratch the surface. Though, Gartner does offer these strategies in competing for talent. The demand for top talent and the scarcity of it hasn’t diminished, but with a few tweaks to your planning strategy, you can lay the groundwork for attracting great employees. If you’re an employee hoping to broaden your range, open to new technologies as well as reaching out in a department not your own, and a team motivator. You might be a ‘unicorn’ employee. Somewhere between the two, we hope you’ll meet and in next year’s guide, development and diversification won’t be quite as at odds with each other. Companies need to remember candidates are stakeholders in the hiring process. Candidates need to remember sometimes it comes down to education. Educate the company how you can best serve them. That question they ask – why do you want to work for this company? This is where you ‘wow’ them and educate them to your why. Be flexible in your hiring and consider flipping from top-down to manager-centric in a bottom-up approach. After all, who is better positioned to offer insights into how jobs are changing and the skills required for it. If you’re looking for a unicorn, or to make your mark on a company, check out our current vacancies or get in touch with one of our experts consultants to learn more. 

William Wrigley

William Wrigley

18. July 2019

Data & Analytics in Munich

Three Reasons Why Munich Is The Place To Be For Data Analysts

As one of the world’s largest economies, Germany continues to attract tech talent from all over the world, and has even overtaken the UK in terms of intra-Europe tech immigration in recent years. Whilst Berlin may be the first place that comes to mind when thinking of places to live as a Data Analyst in Germany, with its numerous start-ups and international culture, there are several reasons why you should also consider the southern gem of Munich. Here are three of the best: A First-Class Quality Of Life While the first thing that comes to mind when thinking of Munich is often the world famous Oktoberfest and the beer induced crowds packed into small beer tents paying the equivalent of a year´s salary for a pint, this is not the only thing Munich has to offer. During the other 349 days of the year when Munich is not packed with Lederhosen-wearing crowds from all over the world, it is a tranquil, green place to live.  Munich is home to a number of large parks, including the beautiful Englischer Garten, Museums and a number of non-beer related cultural events throughout the year. It’s also the third largest city in Germany and, as such, has all the benefits that big city life has to offer. However, nature is never far away, with a beautiful mountain landscape just on the horizon, including the tallest mountain in Germany, the Zugspitze, which sits only 90 km away. On top of this, the transportation system in Munich is one of the best in the country; clean, efficient and so simple to use, it actually makes commuting bearable.  Expansive Opportunities  Most major European cities have seen a boom in the tech market in recent years and Munich is no exception. Not only home to some of the biggest global and German players such as Amazon, MunichRE, Man, Allianz and Linde, the city is also seeing an increasing amount of investment in tech start-ups.  This has led to tech talent, particularly Data & Analytics talent, being highly sought after by a number of the country’s biggest and best employers. And healthy competition means even healthier salaries. Even though Munich doesn’t have the lowest cost of living around, the average pay for Data Analysts is higher than in most other German cities, meaning you’ll get to make the most of your time away from the office.  A Thriving International Culture With 25-38% of Munich´s residents originating from other nations, more and more companies, big and small, are open to welcoming English speakers into their teams. While the culture in Munich still makes it easy to immerse oneself into the German language and culture, the city is also very welcoming to its international inhabitants.  Of course not everyone can speak English, but it is surprising how many people do. This makes getting around as a non-German speaker that much easier, especially considering that the Bavarian version of German can sometimes feel like a completely different language to what is spoken by the rest of the country.  Like every country, different cities attract different personalities and find the right place for you is crucial before making a move. But, with its high quality of life, great job prospects and international culture, Munich certainly has a lot to offer for any Data Analyst looking to move to or within Germany.  If you’re considering making a move to Munich, take a look at our latest opportunities, or get in touch and we can discuss what could work best for you. 

Denise Bachofer

Denise Bachofer

11. July 2019

Our New Berlin Office

We've launched two new offices

I'm incredibly pleased to announce that this week we have launched two new offices.  The first, in central Berlin, will solidify our on-the-ground presence in the German capital and allow us to continue to develop our client base in this rapidly-growing market. Run by Senior Manager Peter Schroeter, under the guidance of our Director of Europe, Alex Hutchings, we're really excited to see the new space become a hub for Berlin's Data & Analytics talent.  Secondly, we've also opened a second Wimbledon office. Despite only moving in to our current home 18 months ago, our rapid growth has led to us opening an additional Executive Office to house our Operations team as we bring in more and more expert consultants. Fortunately, it's just over the road, so there's no need to grab a bus between meetings.  This continues to be a great time for Harnham and watch this space for more growth news in the not too distant future. 

David Farmer

David Farmer

09. July 2019

Machine Learning: How AI Learns

Machine Learning: How AI Learns

Amazon has begun curating summer reading lists. How? Patterns. Facebook shows you ads for items you may have been searching for online. How? It learns from your browsing habits. Ever wondered how Facebook knows you were just looking at that pair of shoes or that particular guitar. The Data you feed it, feeds its brain. In other words, this is how Artificial Intelligence learns. Machine Learning. Whilst it can be disconcerting to know that a machine understands our buying habits, that’s not the only thing it’s used for. It’s also a pivotal tool in such areas as Bionformatics, Biostatistics, Computational Biology, Robotics, and more.  What is Machine Learning? Ultimately, it’s a method of Data Analysis which helps to automate model building and is part of Artificial Intelligence. In other words, it helps to solve Computational Biology problems by learning from Data to identify patterns and make decisions with little human intervention. This helps scientific researchers learn about many aspects of biology. However, running a Machine Learning project can be difficult for beginners, who may experience issues when trying to navigate the information without making mistakes or second guessing themselves. This is one of the reasons a Computational Biologist might want to upskill with a course or two in Machine Learning for a more robust understanding of the information being learned and applied.  The Good News and the Bad With each shift of industrial revolution, there has been one system which has made an indelible mark on our daily lives and the Fourth Industrial Revolution is no different. Just like we can no longer imagine factories without assembly lines, we can also no longer imagine not having Siri, Google Maps, or online recommendations. But, as exciting and as important as these things are, Machine Learning has become so crucial to our daily lives, so complex, it takes a technology expert to master it leaving it nearly inaccessible to those who could benefit from it. Why is Machine Learning Important? By building models to peel back the layers and discover connections, organisations can more easily and more quickly make improved decisions with little to no human intervention. Computational processing is both more affordable and more powerful. It’s possible to quickly scale and produce models which can analyse bigger and more complex data and there’s also a chance to identify opportunities and to help avoid any unknowns such as risk. Machine Learning is used in every industry from Retail to Financial Services to Healthcare. Here are just a few ways it has already transformed our world. Retail – Retailers are able to learn from their customers buying habits, predictive buying habits, how to personalise a shopping experience, price optimisation, and customer insights.Financial services – Machine Learning helps to prevent fraud and identify Data insights.Healthcare – Wearable devices allow for real-time data to assess a patient’s health. Medical professionals can also more quickly find red flags which can help improve diagnoses and treatment.Oil and gas – It cannot only help find where oil might be, but also predict refinery sensory failure, and streamline distribution.Transportation – Help to make routes more efficient and predict problems that could affect the bottom line. While humans can create at least one or two models a week; Machine Learning can create thousands.  Ultimately, the goal of Machine Learning is to understand the structure of Data. As it learns to determine what Data is needed for its structure, it can be easily automated and sift through Data until a pattern is found. This is how machines learn. If you’re looking to take your next step in the field of Machine Learning, we may have a role for you. Take a look at our latest opportunities, or get in touch to see if we can help you take that next step.

Luke Frost

Luke Frost

04. July 2019

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