Research Panel Manager
London / £36 - £450
£36 - £450
Research Panel Manager - Contract
£350-£450 per day - Inside IR35
London - Hybrid
Our client is a leading media company with a reputation for producing high-quality content across various platforms. The client is committed to delivering insights and analytics to enhance its audience's experience and is looking for a Research Panel Manager to join their team.
We are seeking a Research Panel Manager who will be responsible for managing our client's research panel to ensure we deliver valuable insights for our content strategy. The successful candidate will work closely with the research team and other stakeholders to manage the panel's daily operations, including recruitment, engagement, retention, and data analysis.
Role & Responsibilities:
- Manage and oversee the research panel's recruitment, engagement, and retention strategies.
- Develop and execute research projects that deliver insights to drive content strategy.
- Ensure the timely delivery of research data, analysis, and reports to stakeholders.
- Monitor panel activity and performance to ensure we meet research goals.
- Collaborate with other stakeholders to understand research needs and develop effective research methodologies.
- Ensure compliance with data protection regulations and industry standards.
Skills & Experience:
- Proven experience in managing research panels, with at least 3 years of experience in a similar role.
- Experience with research tools such, ideally Qualtrics, however, similar platforms could be considered
- Excellent communication, analytical, and project management skills.
- Knowledge of research methodologies, survey design, and data analysis techniques.
- Ability to work independently and as part of a team.
£350-£450 per day, inside IR35, hybrid, 3 month contract
How to Apply
Register your interest by sending your CV to Lloyd Dunstall via the Apply link on this page
Panel Manager / Panel Management / Research / Media / Qualtrics
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?
Weekly News Digest: 11th – 15th July 2022 | Harnham Recruitment post
This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics.
Tech To Freedom: Five habits of insanely productive software engineers
Software Engineering is a very special expertise, not to mention that it boasts some of the highest salaries around. Of course, as with all roles, years of experience can make a software engineer more efficient, but Tech for Freedom identify five tips for boosting your productivity, even if you’re just starting out. Here are just a couple: Learning by doing: Technology is evolving very quickly, so for a software engineer there is no time to rest on their laurels, they must be constantly learning. The speed of industry developments means that professionals don’t tend to have time to read hundreds of articles or take numerous courses in order to learn something new, instead they are likely to jump into the deep end and learn by doing.
Asking for help
It would be impossible for any one person to know everything. So, one of the essential survival skills for software developers is knowing how to ask for help.You may have ten years’ worth of Python programming under your belt, but now you need to develop something using a special module/tool/framework that you have never used before. The most efficient way to solve your problem is to employ help from someone who does have the experience in that tool. A good engineer knows that titles like ‘junior’ and ‘senior’ do not hold much weight, every engineer, no matter what title they have, has a unique knowledge and experience.Read further insights here.
Wealth Professional: Financial firms can't agree on how to address climate risk
While the risk to financial firms from climate change is considered a top priority, Bloomberg’s poll of 100 executives from financial services firm shows that there is still some way to go to address it.The survey revealed that while 85 per cent of firms have begun to assess the impact of climate risk, there is no consensus on how it should be embedded into risk management frameworks. Of these, 37 per cent are still in the early stages of planning how to incorporate climate risk into models and governance.When asked about the results, Zane Van Dusen, Head of Risk & Investment analytics products at Bloomberg, said: "…even those who say they have a robust model will be making significant changes over the next few years as our understanding and consensus around climate risk grows… More and better data will go a long way toward improving firms' ability to manage climate risk."Find out the key sticking points for the respondents here
The New Statesman: How data can help revive our high streets in the age of online shopping
High streets and town centres across the UK have undergone substantial transformations in recent years. Falling footfall, lost revenues and mounting fixed business costs have had a negative impact on traditional ‘bricks and mortar’ retailers, triggering a large wave of insolvencies across the UK.At the University of Liverpool, researchers have been utilising data and advanced geospatial algorithms to provide various retail-related research outputs and data products. The work is essential for the systematic monitoring of the performance of UK retail centres, giving the team a better understanding about retail centre exposure to current societal and market driving forces. Which will then allow them to track and predict the evolutionary trajectories of any given high street. As a result, in Liverpool they have estimated two types of retail catchments: drive times and walking distances, and then created profiles of those catchments based on numerous measures including deprivation, exposure to internet sales and geodemographics. It is hoped that these tools will aid policymakers, at both a local and national level, in making the decisions that will help revive flagging high streets and level up communities across the UK.Read more here.
Technology Works: AI Reliably Predicts Structure of RNA Molecules
The three-dimensional structure of biomolecules is crucial to their function. Therefore, researchers are interested in knowing more about their spatial structure, and with the help of artificial intelligence (AI), bioinformaticians can already reliably predict the three-dimensional structure of a protein from its amino acid sequence.But for RNA molecules (ribonucleic acid) this technology is still very underdeveloped. Researchers at Ruhr-Universität Bochum have found a way to use AI to reliably predict the structure of certain RNA molecules from their nucleotide sequence.“Identifying these self-similarities in an RNA sequence is like a mathematical puzzle”, explained researcher Vivian Brandenburg. The biophysical model for this puzzle cannot consider the cellular environment of the RNA – in other words it cannot process everything around the RNA.This is where AI comes into the mix. The AI can learn subtle patterns from the cellular environment based on known structures. It could then incorporate these findings into its structural predictions. But for this learning process, the AI needs sufficient training data – and this is lacking.To solve the problem of missing training data, the team used a trick. By working with known RNA structural motifs, researchers used a ‘reverse gear’ to allow them to generate almost any number of nucleotide sequences from the energy models of these structures, that would fold into these spatial structures. With the help of this ‘inverse folding’ the researchers generated sequences and structures with which they could train the AI.Find out if the process worked here.We've loved seeing all the news from Data & Analytics in the past week, it’s a market full of exciting and dynamic opportunities.
To learn more about our work in this space, get in touch with us at email@example.com.
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