London / £300 - £400
£300 - £400
£300-£400 per day
London and Amsterdam
A large UK-based hospitality client with a portfolio of inner city and outer city attractions around the world is searching for a Revenue Manager to join the European team. Our team is dedicated to providing exceptional service to our guests, while also achieving our financial goals. We are seeking a Revenue Manager to join our team on a 3-month contract basis to help us maximize revenue and profitability during a busy season.
As our Revenue Manager, you will be responsible for developing and executing revenue management strategies for our attractions. You will work closely with the sales, marketing, and operations teams to forecast demand, set pricing, and optimise inventory to achieve maximum revenue and profit. You will also analyse market trends and competitor pricing to ensure we are offering competitive rates and packages.
Role & Responsibilities
- Develop and execute revenue management strategies for our attractions
- Analyse market trends and competitor pricing to optimise pricing and inventory
- Work closely with sales, marketing, and operations teams to forecast demand and set pricing
- Monitor and adjust pricing and inventory based on demand and market conditions
- Provide regular revenue and performance reports to management
- Develop and maintain strong relationships with online travel agencies and other distribution channels
- Implement and manage revenue management systems and tools
- Participate in revenue strategy meetings and provide input on pricing and inventory decisions
- Conduct training sessions with hotel and resort staff on revenue management best practices
Skills & Experiences
- Background in revenue management in the hospitality, travel or retail environment
- Strong analytical skills and the ability to interpret and apply data to drive revenue
- Excellent communication skills and the ability to build relationships with stakeholders at all levels
- Experience with revenue management systems and tools, such as Opera, IDeaS, or Duetto
£300-£400 per day, travel to Amsterdam
How to Apply
Register your interest by sending your CV to Lloyd Dunstall via the Apply link on this page
Ten Tips for Writing the Perfect Data & Analytics CV | Harnham Recruitment post
It’s no secret that jobs within the Data & Analytics market are more competitive than ever and with some jobs having hundreds of applicants (if not more), having a CV that stands out is more important than ever. It’s well known that many Hiring Managers spend a short amount of time reviewing a candidate, so you need to consider what they can do to have the best impact. We’ve seen it all over the years, from resumes sorely lacking detail through to those that have almost every accomplishment written over too many pages – so we’ve complied a list of the 10 things that could help you create a resume that makes an impact, complete with top tips from our team of experienced recruiters.1. Keep it Simple All of our recruiters are unanimous in suggesting to candidates that the perfect CV length is no more than two pages, or one for a graduate or more junior candidate. Sam, our Corporate Accounts manager suggests that candidates keep it simple:“In analytics, it’s all about the detail and less about how fun your CV looks. My best piece of advice would be to keep it to two pages, use the same font without boxes or pictures, and bold titles for the company and role. It sounds pretty simple but it’s really effective and often what our clients seem to be drawn to the most”. 2. Consider the audience & avoid jargon Before your CV gets to the Hiring Manager, it may be screened by an HR or recruitment professional so it’s crucial to ensure that your CV is understandable enough that every person reviewing it could gauge your fit. Whilst showing your technical ability is important, ensure that you save yourself from anything excessively technical meaning only the Hiring Manager could understand what you have been doing. 3. Showcase your technical skills There is, of course, a need to showcase your technical skills. However, you should avoid a long list of technologies, instead clarify your years of experience and competence with each of the tools. Within the Data & Analytics market specifically, clarifying the tools that you used to analyse or model is very important and writing those within your work experience can be very helpful. Wesley, who heads up our French team, explained where candidates can often go wrong: “Candidates often write technical languages on their CV in long lists and forget to make them come to life. My clients are looking for them to give examples of how and when they have used the listed tools and languages”4. Consider the impact of your workJust writing words such as ‘leadership’ or ‘collaboration’ can often easily be over-looked. It’s important that you are able to showcase the impact that you work has beyond the traditionally technical. Think about how you can showcase the projects that you have lead or contributed to and what impact it had on the business. Often people forget the CV isn’t about listing your duties, it’s about listening your accomplishments. Ewan, our Nordics Senior Manager brings this to life: “I would always tell someone that whenever you are stating something you did in a job you always follow up with the result of that. For example, ‘I implemented an Acquisition Credit Risk Strategy from start to finish’ – but then adding, ‘which meant that we saw an uplift of 15% of credit card use’”. Joe, New York Senior Manager, concurs: “Actionable insights are important, results driven candidates are what our clients are looking for. So instead of ‘Implemented A/B Testing’, I’d get my candidates to make that more commercial, such as ‘Implemented A/B test that result in 80% increase in conversion’”. 5. Use your Personal Summary A personal summary is effective when it comes to technical positions, as some people can often overlook them. Use this to summarise your experience and progression as well as indicate the type of role and opportunity you are looking for. If this is highly tailored to the role you are applying for, it can have an extremely positive impact. For example: ‘Highly accomplished Data Scientist, with proven experience in both retail and banking environments. Prior experience managing a team of five, and proven ability in both a strategic and hands on capabilities. Proven skills in Machine Learning and Statistical Modelling with advanced knowledge of Python, R and Hadoop. Seeking Data Science Manager role in a fast-paced organisation with data-centric thinking at it’s heart’. 6. Consider what work and non-work experience is relevant If you’ve been working in the commercial technical sphere for more than five years, it’s likely that your part time work experience during university or the non-technical roles that you took before you moved into your space are no longer as relevant. Ensure you are using your space to offer the Hiring Manager recent, relevant and commercially focused information. However, do not leave gaps just because you took a role that didn’t relate to your chosen field, you don’t need to describe what you did but have the job title, company and dates to ensure you are highlighting a clear history of your experience. It’s important to note that you are more than just your work experience as well, Principal Consultant Conor advises candidates to talk about more than just their work accomplishments:“Listing non work achievements can help make the CV stand out. If someone has a broad range of achievements and proven drive outside of work, they will probably be good at their job too. Plus, it’s a differentiating point. My clients have found interesting talking points with people who have excelled in sports, instruments, languages and more specifically for the Analytics community – things like maths and Rubik’s cube competitions”. 7. Don’t forget your education For most technical roles, education is an important factor. Ensure that you include your degree and university/college clearly as well as the technical exposure you had within this. If you did not undertake a traditionally technical subject, make sure you highlight further courses and qualifications that you have completed near this section to highlight to the Hiring Manager that you have the relevant level of technical competence for the role. 8. Don’t include exaggerated statementsIt goes without saying that if you are going to detail your experience with a certain technical tool or software that you could be asked to evidence it. Saying your proficient in R when you’ve done a few courses on it won’t go over well, especially if there are technical tests involved in the interview process. At the same time, don’t undervalue your expertise in certain areas either, your strengths are what the Hiring Managers is looking for. 9. Don’t get too creativeUnless you’re in a creative role it’s unlikely that the Hiring Manager will be looking for something unique when it comes to the CV. In fact, very few people can pull of an overly flashy CV, most of them being those that work specifically in design. When in doubt, stick to standard templates and muted tones. 10. Tailor, Tailor, Tailor! Time is of the essence and when it comes to reviewing CVs and you don’t have long to make an impact. Make sure to customise your resume using keywords and phrases that match the job description (if they match your own, of course). For example, if the role is looking for a Business Intelligence Analyst with proven skills in Tableau you would not just claim, “experience in Data Visualisation”, you’d list the software name, “experience in Tableau based Data Visualisation”. Although every job description is different, all it takes is a few small tweaks to ensure your maximising your skillset. If you’re looking for your next Data & Analytics role or are seeking the best candidates on the market, we may be able to help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more.
Hiring a BI Manager – Trends and Challenges | Harnham Recruitment post
With all the talk of big data and data science being able to predict what colour shirt I will buy in four years’ time (probably white or blue for those who don’t know me!), effective business intelligence is sometimes passed by or considered old news. The reality is that companies are realising that they can get much more from their business intelligence and are changing their strategies to deliver interactive, insight-driven and visualised reports. Not every data-driven decision needs machine learning algorithms behind it, and quality business intelligence enables all managers to be effective decision-makers. These strategies are creating some obvious trends in the market, resulting in a change in expectations when hiring a BI Manager. Key BI TrendsData Visualisation – Companies of all sizes are implementing Qlikview and Tableau (amongst many other tools) to create attractive, interactive visualisations, to harness intelligence, in a way that will capture attention in a presentation. Insight Driven – A BI professional can’t simply develop automated reports anymore. Analysts are often required to offer suggestions for business change and present insight to decision makers. Hands-on Management – BI managers and even heads of business intelligence are expected to keep coding well into their management years, with the logic that problems can be spotted quicker when they are in the trenches, coupled with strategic and line management work. Data Ambassadors – BI professionals are becoming door-to-door data sellers, coaching teams in a business on the benefits of using data to optimise their teams and decisions to save or bring in more money. Heads are in the Cloud – Companies are using cloud-based data warehouses such as Redshift to save on storage costs, whilst creating a centralised data warehouse for BI. Alternative Data Sources – Companies are looking to use the web and social media data, alongside numerous other sources to generate deep insights for managers. The BI Manager EffectI am completely sold that all of these features represent the future of business intelligence. The few companies that are doing all of the above well enough, are doing advanced work in the area and these companies will be leveraging big commercial gains from their business intelligence teams. The problem is that only a few businesses are doing all of the above, so only a handful of professionals have the relevant experience, and as a result expect top dollar to bring all of those skills. Therefore, it is prudent to be flexible with your hiring requirements. Look for a bright, passionate candidate, who can readily grasp the shift in business intelligence trends, and is keen to plug skills gaps. An enthusiastic business intelligence professional will get up to speed with whatever they were missing. Don’t be too quick to dismiss those who are not ready-made BI managers on paper. Message to CandidatesFor all aspirational or existing business intelligence managers and leaders, I would advise you try to stay hands on as long as possible. I know some of you dream of never seeing a line of SQL code again, however, the trend in hiring for hands-on business intelligence management positions means that keeping your tech skills sharp will really keep your options open moving forward. It would be great to hear your experiences, so please feel free to comment below on the trends you see in your business. Have you needed to remain hands on as you progress within your career? Or are you looking for a multi-skilled BI manager, and it is proving hard?
How To Lead A Data Team | Harnham US Recruitment post
Dream teams from sports to business are an ideal everyone aspires to live up to. But what is it every basketball or football dynasty has which makes them a dream team? What is it that brings individuals together to overcome odds, set examples, find solutions, and create the next best thing? Good management. The need for good management is no different in the Data Science world. Yet according to our latest Salary Guide, poor management is one of the top five reasons Data professionals leave companies. So, let’s take a look at what poor management is, what causes it, and how businesses can better retain Data talent.
What’s Your Data Science Strategy?Most businesses know they need a Data team. They may also assume that a Data Scientist who performed well can lead a Data team. But that isn’t necessarily the case. Managers have to know things like P&L statements, how to build a business case, make market assessments, and how to deal with people. And that’s just for a start. The leader of a Data team has a number of other factors to consider as well such as Data Governance, MDM, compliance, legal issues around the use of algorithms, and the list goes on. At the same time, they also need to be managing their team with trust, authenticity, and candor. The list of responsibilities can be daunting and if someone is given too much too soon and without support, it can be a recipe for disaster.Other businesses might believe that a top performing Data Scientist would make a good manager. Yet these are two different fields. Or you might look at it this way. If you are willing to upskill a top-performing Data professional and train them in managerial skills, giving them the education and support they need, that is one solution.Another solution is to create a Data Science strategy which brings in people with business backgrounds. Data Science is a diverse field and people come from a number of backgrounds not just Computer Science or Biostatistics, for example. Now that you’ve seen what might cause a manager to fail, let’s take a look at a few tips to help you succeed.Seven Tips for Managing a Data TeamManaging a team is about being able to hire, retain, and develop great talent. But if the manager has no management training, well, that’s how things tend to fall apart. Here a few tips to consider to help ensure you and your team work together to become the dream team of your organization:Build trust by caring about your team. Help define their role within the organization. Ensure projects are exciting and that they’re not being asked to do project with vague guidelines or unrealistic timeframes.Be open and candid. Remember, Data Scientists are trained in how to gather, collect, and analyze information. If anyone can see right through a façade, it will be these Data professionals. Have those “tough” conversations throughout every stage of the hiring, onboarding, and day-to-day, so that no one is caught unaware.Offer consistent feedback. And ask for it for yourself as well from your team.Ensure your team understands the business goals behind their projects. Let them in on the bigger picture. Think long-term recruitment for a permanent role, not short-term. If you have an urgent project, consider contracting it out. Prioritize diversity to include academic discipline and professional experience. Does the way this person view the world expand the knowledge of your team’s knowledge? Dream teams don’t always have to agree. Sometimes, the best solutions are found when there are other opinions.Finding the perfect, “Full Stack” Data Scientist or Data Engineer or Analyst is not impossible, and retaining them can be even easier. If you’ve done your job well, your team will trust you, have a balanced skillset, and understand how their work supports the organization and its goals. For more information on how to be a great manager, check out this article from HBR. Ready for the next step? Check out our current vacancies or contact one of our recruitment consultants to learn more. For our West Coast Team, call (415) 614 – 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast Teams, call (212) 796 – 6070 or send an email to email@example.com.
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