Sam Maughan - Recruiter Profile | Harnham Recruitment

This website uses cookies. By continuing to use this site, you are giving your consent to cookies being used. See our Privacy policy for more info.

Jobs

Specialism
About
Clients
Join Us
Contact

Login / Register

Login

Login using your social profile

Email

Password

Remember Me

Register a new account with Harnham

Forgot your password?

Email Please supply a valid email Please supply a valid email

Please check your email inbox. If we were able to find an account using the email address you provided, we will have sent instructions to you on how to reset your password. If you have not received anything after an hour or so, it may mean you entered your email address incorrectly or do not have an account with us.

Sam Maughan

Senior Manager - UK

Bio

Sam joined Harnham in 2014 as part of the Risk Analytics team. After two years he relocated to New York to help set up Harnham’s Risk Analytics presence in the US. After a successful two years Sam returned home to the UK where he now manages the major accounts team at our Wimbledon headquarters!

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 Write The Perfect Tech Job Description

It’s a challenge finding the right Data & Analytics candidate. Add in the number of companies fighting for that perfect profile and for many it can seem like an uphill battle. But there’s a simple way to cut through the noise; better job descriptions. As a specialist recruitment agency within the Data & Analytics space, we have seen a real variety of job descriptions over the years, from the bright and innovative to the long and technical. And it may surprise you to learn that candidates still ask regularly to see official job descriptions and it is part of their decision-making process. Unfortunately, they are also often a part of the recruitment process that can be rushed or created from out-of-date previous descriptions. There are some real benefits, however, to putting the time and effort required into creating something fresh. If you’ve recruited a role like a Data Scientist before, you know that the problem isn’t usually getting enough candidates through the door, it’s about getting the right ones. A well-crafted job description leads to better quality applicants. It also helps those candidates become more engaged and excited about your business. So, with that in mind, here are our five top tips for businesses looking to help their role stand out from the crowd. CHECK YOUR JOB TITLE You might think that calling your BI Analyst a ‘Data Ninja’ is going to get you the top talent, but it would probably mostly cause confusion. It is important that you align the job title to a clear and market relevant job title. Often internal job titles can be the biggest blocker in aligning your vacancy to the market. Consider changing the job title for external purposes to make it more closely aligned to the market. Here are some common examples: An AVP Analyst within a Marketing Analytics team is more closely aligned to a Senior Marketing Analyst. A Data Scientist job title aligned to a role with no machine Learning or algorithmic development may be better titled a Statistical Analyst. CREATE A COMPELLING JOB RUN-THROUGH Our consultants agreed unanimously that one of the weakest areas of job descriptions tends to be the more detailed description of what the role actually is. Too often job descriptions just list lots of different responsibilities, but these are often very generic or basic. Before starting to write the job brief, ask members of your team that do the role already – what gets them excited? You will likely find that it has to do more with the types of projects i.e. the application of technical elements, that appeals most to candidates. If you can, bring the role to life in a meaningful way. For example, relating it to projects that your team has done is a really enticing method of exciting a candidate about the potential of the role. Create A Tailored Experience Section Uninspiring job descriptions often have long lists of key skills required, often with irrelevant skills included. Keep your requirements to around 5 or 6 key bullet points, asking yourself what the most important requirements are and clearly laying those out. On top of that often companies get too focused on requesting years of experience. We strongly discourage companies from specifying years of experience in a job advert as, within the UK, most European countries and a number of US states this is classified as age discrimination. Instead of including years of experience, carve out what it is that you want your ideal candidate to have done before instead, this will often correlate to their experience level. For example: 5+ years' experience in a Marketing Analytics could easily be transformed to Proven commercial experience in a Marketing Analytics environment with exposure to pre and post campaign analysis, customer analysis, customer segmentation and predictive modelling. DON’T FORGET TO SELL YOURSELVES Another key area where many companies fall down is effectively selling their opportunity and company to the prospective candidates. Whether an active or passive job-seeker, candidates are likely deciding whether this is the right fit for them based on what they are reading. Many job descriptions completely forgo any type of sales pitch above an initial description of what the company does, perhaps because they expect the candidate to know them and want them. These are the areas we’d suggest bringing to life to effectively sell your opportunity: Writing in your brands personality. Consider the right tone of voice to match your company culture and style of working. Introduce yourself. Whether you’re a brand name or not, use this chance to actually tell people about what you really do and what you really stand for. Share what it’s like to work for the company. Include the culture, work environment, targets, challenges and of course reference to perks and benefits on offer too. Consider the candidate. What appeals to a talented Data Scientist will differ from what appeals to an HR professional. Make sure you tailor your overall pitch to the type of candidate you are seeking. WORK ON THE LOOK AND FEEL A little effort on the aesthetic look of your job description an go a long way. On top of a nice overall look, keep the length to a maximum of 1.5 pages. Utilise bullet points and bold formatting to keep the description some-what ‘skimmable’. If you’re looking to hire a Data & Analytics professional, Harnham can help. Get in touch with one of our expert consultants to find out more.

by Sam Maughan

14. May 2020

NADAL OR DJOKOVIC? COULD YOU PREDICT THE WINNER?

Most pundits will have an opinion on who will triumph in this year's US Open men's final - Rafael Nadal or Novak Djokovic - but the best insights into who will be crowned champion will come from the same technology that has helped cities to lower crime rates and plan for extreme weather.Deep in the bowels of Arthur Ashe Stadium in Flushing Meadows, Queens, New York, beats the data heart of the 2013 US Open.In a bland room accessed through an unmarked door, more than 60 laptops are piled high, arranged like a command control center for a mission to the moon.This room is known as "scoring central", according to US Open officials.It's where data is pushed to scoreboards on Louis Armstrong Court - the second largest US Open tennis court - or to TV screens across the globe.But more than a power processing center, this is where the results of matches are broken down and analyzed, where it's determined not only who won, but why they won, according to the numbers."Say you wanted to see every backhand unforced error in a match. You would touch a button and all of those would come up," says IBM's vice-president of sports marketing, Rick Singer.But seeing what has happened in past matches is rapidly giving way to better predicting what will happen in future pairings, explains Mr Singer.To put it simply: the past might have centered around intuitively understanding that a player who gets a majority of their first serves in will win the match.The future is pinpointing the exact percentile threshold the player must cross to win.'Unusual statistics'This year, IBM has gathered more than 41 million data points from eight years of Grand Slam tennis matches to better understand the small details that end up deciding a match.Djokovic will win if he:Wins more than 57% of 4-9 shot ralliesWins more than 39% of first serve return pointsHits between 63% and 73% of winners from the forehandNadal will win if he:Wins more than 48% of 4-9 shot ralliesWins more than 63% of points on first serveAverages fewer than 6.5 points per game on his own serveSource: IBM The idea is that by crunching more and more data, patterns will emerge that can help better hone predictions.So what should Novak Djokovic do if he wants to beat a resurgent Rafael Nadal, who has emerged this summer as the dominant force on hard courts?Looking at data from the head-to-head matches between the two in Grand Slams, IBM says that if Djokovic wins more than 57% of medium-length rallies (of between four and nine shots) then he will emerge triumphant.He also has to win more than 39% of return points on Nadal's first serve.Nadal, on the other hand, has to dominate on his serve. If he wins more than 63% of points on his first serve then IBM predicts he will win.However, the longer Nadal's service games go on, the less likely he is to win. He needs to keep his service games relatively short, averaging fewer than 6.5 points per game, according to IBM."It's the same sort of statistical analysis and predictive analytics that we do for our clients all around the world, just applied to tennis," explains Mr Singer."What we're trying to do is find statistics that are unusual."A backhanded solutionDjokovic, for instance, must focus on getting his backhand into play.According to IBM's data, when Djokovic can hit his backhand deep to Nadal's forehand, his odds of winning the point dramatically increase.However, during this tournament that stroke has been particularly difficult for Djokovic - he's had 32 backhand winners, but 70 backhand unforced errors.For Nadal, he will go into the final knowing that his most powerful weapon - his forehand - is working well. He has hit 113 forehand winners, compared with Djokovic's 73.He will also know that as long as he can continue to keep up his variety of serve, and go to the net occasionally - where he's won 81% of the points he has played there - he might have the upper hand over Djokovic.Serbia's world number one will also have to improve his consistency in the final. Although both players have hit the same number of winners in the tournament so far (206), Djokovic has made 167 unforced errors, far more than Nadal's 130.And with the Spaniard having dropped serve just once all tournament, Djokovic will have to be more ruthless when taking any break point opportunities that come his way, having converted only 44% up until now.Elephant brainIt's only with the advent of big data technologies and faster, better, processing power that companies like IBM say they've been able to quickly and cheaply gather these new insights.Most of these big data crunching technologies, from predicting airline prices to sports champions, use something known as Apache Hadoop.Designed by engineers who had been working at Yahoo and elsewhere ("Hadoop" was the name of one of the creators' son's toy elephant), it is now just one of the components of IBM's predictive analytics toolkit.The hope is that in the future, statistics like these might not just be of benefit to sports as a whole, but that athletes themselves will be better able to calibrate their performances."Each tournament we evolve a little bit further," says Mr Singer.The goal, he says, is "to take the statistics beyond what people are expecting".But for fans watching the US Open final who have no head for statistics, Rafael Nadal's coach and uncle, Toni Nadal, has this simple advice for what it takes to succeed: "You should play good, nothing else. You should play very well." Click here for the article on the web.

by Sam Maughan

21. January 2015

EDWINA DUNN AND CLIVE HUMBY TO JOIN STARCOUNT

The husband-and-wife team who made more than £90m from helping Tesco understand what customers put in their shopping baskets are turning their hands to tailoring brands to individual users on the likes of Twitter and Facebook.Edwina Dunn and Clive Humby – who sold their Dunnhumby business to the supermarket giant for £93m – are to join the board of social network analytics firm Starcount.The pair are selling their private vehicle, H&D Ventures, to Starcount for an undisclosed sum, taking a stake in the business as part of the deal. It comes alongside a $5m (£3.25m) fundraising for Starcount, with new investors including Artemis Capital and Praetura Capital.In addition, Christopher Carter, former vice-chairman of institutional securities at Morgan Stanley, is joining Starcount’s board as chairman. He is also one of the new investors in what is the company’s third equity fundraising. Starcount is run by chief executive Drew Thomson, who remains in the role.Ms Dunn and Mr Humby set up H&D Ventures 18 months ago to continue their business interests in data mining following their exit from Dunnhumby. Since then, they have worked on a mobile data project for one of the country’s largest mobile networks, and looked at the different ways of using data from social networks. Ms Dunn described the move as her and her husband’s “big play”, referring to it as a “quantum leap” from their work with Tesco.She said that brands and companies tended to be poor at marketing to individuals via social networks.“In a way, we’ve gone back to mass marketing – everyone gets the same tweet or blog,” she said. “With the data that are available, we can look specifically at the people who influence others, and we can make ambassadors of them for brands and celebrities.”The duo began working with Tesco in 1995, helping use its Clubcard loyalty scheme to understand what its customers were buying, and how to attract them back to its stores. They stepped down from executive roles at Dunnhumby at the end of 2010. Click here for the original article on the web.

by Sam Maughan

08. August 2013

View all blogs

recently viewed jobs

Giving Back

Read about Harnham's corporate social responsibility initiatives

Find our more about the causes we support.

READ MORE

RECRUITMENT
ABOUT US
CONTACT
OTHER

© 2018 Harnham Search and Selection Ltd. All rights reserved

Registered office: 3rd Floor, Melbury House, 51 Wimbledon Hill Road, Wimbledon, SW19 7QW.
Harnham Search and Selection is a registered company in England and Wales. Company registration number: 05723485

Website by Attrax / Designed by Brand Nu

User Profile Page

Keyword: No Keyword

Options: 652, 1142

Location: US