Harnham

Harnham US Data & Analytics Salary Guide 2019

The definitive source of salary information for the US Data & Analytics market



From providing an overview of average salaries, to an analysis of the latest trends, technologies and threats to the market, this guide is designed to educate and inform as we look to continuously improve the Data & Analytics space in the US. 

Simply complete the form below to download our US Salary Guide. We may get in touch to hear your thoughts and ask for feedback on our most extensive Guide to date.

Clear

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.

The Harnham 2019 Data & Analytics Salary Guide Is Here

We are thrilled to announce the launch of our 2019 UK, US and European Salary Guides. With over 3,000 respondents globally, this year’s guides are 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 77% of respondents in the UK and Europe, and 72% in the US, willing to leave their role for the right opportunity.  Salary expectations remain high, although we’re seeing that candidates often expect 2-10% more than they actually achieve when moving between roles.  Globally, 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 UK market is only 25% female and this falls to 23% in the US and 21% across the rest of Europe.  In addition to our findings, the guides also include insights into a variety of markets and recommendations for both those hiring, and those seeking a new role.  You can download your copies of the UK, US and European guides here.

David Farmer

David Farmer

10. June 2019

HOW BRANDS USE DATA TO CREATE SUCCESSFUL CAMPAIGNS

Make no mistake: making minor adjustments to an ad or campaign that’s meant to appeal to the masses just won’t cut it. Customers crave creativity. They want to be understood. Which is why people respond best to brands that do their homework, doing their research into what appeals to different groups. How should businesses appeal to their chosen segments, then, considering how diverse people are? Data, of course. Why Data? For one thing, it drives results and creates improved outcomes. Data also helps to prove the value of marketing, providing a bargaining chip for future budget discussions. And, most rewarding of all, brands get valuable insights into their target market. Which, in turn, leads to more well-targeted, profitable campaigns.  And if you think Data doesn’t belong in the world of creative campaigns, think again. As OpenJaw Technologies Chief Marketing Officer Colin Lewis argues: “Creativity is not just compatible with being Data-driven – Data can drive better creative.” Psychological profiling Strategic communications consultancy, Verbalisation, researches and analyses language to form valuable insights. Using its Rapid Audience Insights Diagnostic system, the company’s team of psychologists and researchers work out how an audience thinks. They also learn the actual words an audience uses, which they then use as the basis of a marketing strategy.  Based on their unique research and insights, Verbalisation has created several successful campaigns for high-profile brands. These include the #NotAnotherBrother campaign for counter-terrorism organisation Quilliam, which looked at the motivations of jihadists.  The campaign is now used by the UN and schools across the UK, as well as the US Department of Defense. It is the most viewed counter-extremism campaign of all time, with more than half a billion global media impressions.  Location, location, location Out-of-home (OOH) advertising. Yes, it goes way back, but it’s actually the only traditional advertising channel posting rapid growth. In fact, thanks to mobile-location Data, brands can target audiences quicker and with a greater chance of success than ever before.  Great news for JCDecaux (JCD), a leading OOH company with ads reaching 410 million people in over 4,000 cities. JCD now works with location Data to define and segment audiences. Doing so helps it decide where to place media, improve campaigns and measure resulting store footfall and purchases.  Knowledge, so they say, is power. Particularly when that involves knowing the whereabouts of the most coveted customers. Newly teamed up with identity resolution company, Neustar, JCD’s insights look stronger than ever. JCD can now understand which of its locations rank higher for any brand’s most desired audiences. All thanks to location Data and real-time behaviour analysis.  Personalised employee training Data doesn’t just boost the results of B2C brands; it can also be a vital shot in the arm for internal security training campaigns. Training provider, CybeReady, for instance, uses a Data science-driven approach to deliver cyber awareness training with a difference: its anti-phishing platform helps security teams quickly roll out and tailor campaigns to individual employees. In big companies, getting employees up to speed is especially challenging. With many locations, languages and time zones to contend with, Information Security teams have their work cut out.  CybeReady eliminates these challenges by delivering 12 personalised, 60-second simulations to each employee. In their first language, every year. What’s more, the training provider uses machine learning to analyse performance on a daily basis. This enables it to provide the most appropriate simulations to each individual. The result? IT teams save 160 hours each month and employee resilience increases five-fold. There’s no limit to what Data can do. If you’re a fan, we may have a role for you. Take a look at our latest opportunities or get in touch with our expert consultants.  

Talitha Boitel-Gill

Talitha Boitel-Gill

05. June 2019

The Evolution Of The Data Engineer

Every Data Science department worth its salt has at least one engineer on the team. Considered the “master builders,” Data Engineers design, implement and manage Data infrastructure. They lay down digital foundations and monitor performance. At least, that’s what they used to do.  Over the last few years, the role has shifted. Data Engineers have gone from mainly designing and building infrastructure, to a much more supportive and collaborative function.  Today, a key part of the engineer role is to help their Data Analyst and Data Scientist colleagues process and analyse data. In doing so, they are contributing to improved team productivity and, ultimately, the company’s bottom line. THE IMPACT OF THE CLOUD In the past, a Data Engineer would often move data to and from databases. They’d load it in a Data Warehouse, and create Data structures. Engineers would also be on hand to optimise Data while businesses upgraded or installed new servers.  And then along came the Cloud.  The rapid dominance of cloud computing meant that optimisation was no longer needed. And as the cloud made it easy for companies to scale up and down, there was less need for someone to manage the data infrastructure.   The collective adoption of the cloud has had a big impact on the function of Data Engineers. Because, provided a company has the funds, there is no longer the same demand for physical storage. Freed from endless scaling requests, engineers have more time to program and develop. They also spend more time curating data for better analytics.  AUTOMATING THE BORING BITS  Less than a decade ago, if start-ups wanted to run a sophisticated analytics program, they’d automatically hire a couple of Data Engineers. Without them, Data Analysts and Data Scientists wouldn’t have any Data. The engineers would extract it from operational systems, before giving analysts and business users access. They might also do some work to make the Data simpler to interpret.  In 2019, none of this extraction and transformation work is necessary. Companies can now buy off-the-shelf technology that does exactly what a Data Engineer used to do. As Tristan Handy, Founder and President of Fishtown Analytics, puts it: “Software is increasingly automating the boring parts of Data Engineering.”  STILL SOUGHT-AFTER  With automation hot on the Data Engineer’s tail, it can be tempting to ask whether they are still needed at all.  The answer is: yes, absolutely. When recruiting engineers, Data Strategist Michael Kaminsky says he looks for people “who are excited to partner with analysts and Data Scientists.” He wants a Data Engineer who knows when to pipe up with, “What you’re doing seems really inefficient, and I want to build something better.” Despite the rise in off-the-shelf solutions, engineers still play a key role in the Data Science team. The difference is simply that their priorities and tasks have shifted.  Today, innovation is the watchword. The best engineers are hugely collaborative, helping their teams go further, faster. It’s an exciting time to be a Data Engineer. If you’re interested in this field, we may have a job for you. Take a look at our latest opportunities or get in touch with our expert consultants.  

William Wrigley

William Wrigley

29. May 2019

The Power Of Programmatic: How It Keeps On Converting

Applying to anything from digital out-of-home to mobile, social media to TV, Programmatic tech continues to develop at a furious pace. And as it gets more sophisticated so, too, does its power to fuel growth across multiple industries.  So it goes without saying that Programmatic is set to remain a valuable part of the Ad Tech toolkit. As it evolves, brands can measure and enhance their creative campaigns with ever-greater accuracy to improve conversion rates and engagement. Here are some of the latest ways automated ads have been helping brands increase their influence over customers. SHORTENING THE RETAIL SALES FUNNEL  The former might of traditional brand and advertising agency models is fading. Instead, we’re seeing the old sales funnel being redefined into a more direct buying journey. Omnichannel shopping is now the norm, and screens with their accompanying ads wield plenty of power in influencing how we shop.  Thanks to growing numbers of mobile purchases coupled with Programmatic technology, brands use Data to improve the customer experience, reduce acquisition costs and push more products into online shopping baskets.  And as more retailers prioritise selling stuff online, they gain more control over customer data. Which in turn feeds their automated ads and speeds up the buying journey further. BOOSTING BRANDED CONTENT REACH  No worldwide media corporation would last long without using technology to make the best use of its resources. So it makes sense that the BBC uses Programmatic ads to create greater access to its branded content. Using data, the BBC can see what particular audience segments are into, from trending topics to the devices they’re choosing to devour news and entertainment. From there, the broadcaster twins its own data with wider industry stats to form insights that help to shape its content strategy. Automated media buying also reduces the labour that traditionally accompanied ad campaigns. The key advantage being that it frees up staff to concentrate on more creative tasks, according to Luke Fox, the BBC’s Head of Programmatic for the Asia Pacific. As a direct result of the automated ads, the BBC’s media placement has become more focused and effective, with branded content “getting to the right people at the right time.” An advertiser’s dream come true, essentially.  It is minimal effort, too. Using Programmatic tech gives organisations better access to consumers all over the world, across a wide array of media such as podcasts.  CUSTOMISED MESSAGING We all know that personalisation is a tried-and-tested marketing strategy. So it’s no surprise that programmatic ads adapt to whoever they’re targeting. Ads adapt to multiple audience variants, from age, gender, income and location right down to the device we’re using. Through constant feedback, marketers can adjust their campaigns in real time, changing their message according to where customers are, what they’re doing and how they’re responding to the ad. In theory, as more brands move their media-buying in-house, the Programmatic process becomes easier to control and adapt. Zendesk’s director of digital Aurélien Dubot certainly thinks so. After the company moved its advertising in-house, Dubot says the decision has enabled them to make instant tweaks: “We don’t wait a week or three days to adjust things, we adjust it straight away.” Whether brands choose in-house or an agency for their media buying, one thing’s for certain: programmatic is a complex system that continues to bear fruit, provided brands set clear goals for what they’re trying to achieve. Ultimately, the results will only be as good as the data, along with the marketing team’s ability to analyse it. The Programmatic industry is growing. If you’re interested in Data & Analytics, we may have a role for you. Take a look at our latest opportunities or get in touch with our expert consultants.  

Francesca Harris

Francesca Harris

23. May 2019

Recently Viewed jobs