At a Glance
- Tasks: Analyse social discourse and online behaviour to uncover emerging trends and insights.
- Company: Join SPQR, a global insights firm at the forefront of belief intelligence.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Fast-paced role with potential for significant impact on client strategies.
- Why this job: Be part of a team that drives strategic decisions with real-time insights and AI technology.
- Qualifications: Experience in social listening and strong analytical skills are essential.
The predicted salary is between 40000 - 50000 £ per year.
SPQR is a global insights and strategy firm leveraging PRISM, a purpose-built, AI-powered system designed to identify emerging beliefs and trends. PRISM detects where social discourse and online behaviour indicate the formation or shift of public opinion, providing real-time insights that uncover risks and opportunities before they solidify. Through targeted strategy, content, and campaigns, SPQR enables organisations to act proactively and drive growth.
This is a full-time, on-site role based in Central London. As a Belief Intelligence Analyst, you will monitor, analyse, and interpret emerging patterns in social discourse, online behaviour, and stakeholder sentiment. Responsibilities include performing intelligence analysis, synthesising insights, and generating concise reports to inform strategic decisions. You will collaborate with cross-functional teams to identify risks, opportunities, and actionable insights and deliver data-driven strategies in a fast-paced environment.
You will run the Conversation and Behaviour dimensions day-to-day, across client work and our own market intelligence. That means social listening done properly, monitoring of online behaviour across the places narratives actually form, and the analysis that turns thousands of raw signals into something a board will act on.
You will work with AI throughout. PRISM uses a series of AI agents to clean, classify, and pattern-match data at a scale no human team could match. Your job is to run that pipeline, check its work, and catch the errors and hallucinations before they ever reach a client. AI does the groundwork. You do the thinking. That order does not change.
The best person for this is part analyst, part detective. You can read a dataset and a discussion thread with equal confidence, and you are at your best when you have found the thing nobody else spotted.
What you'll do:
- Run social listening across X, Reddit, Telegram, LinkedIn, forums, review sites, and employee voice platforms such as Glassdoor and Blind. Separate real signal from bots, noise, and the loudest few.
- Track online behaviour: search trends, purchase and petition signals, registered interests, and what LLMs say about a client when asked (our AI visibility work).
- Build and apply classification rules and taxonomies, so the analysis is consistent whoever is running it, and so it holds up when a client challenges it.
- Run PRISM's AI pipeline, quality assure every output, and flag anything that does not stand up.
- Feed clean, classified signal into the triangulation, and help spot the say-do gaps and contradictions that are the point of the whole method.
- Turn findings into clear written insight. Not a dashboard, not a data dump. The 'so what', and what to do about it.
- Help build and present Belief Assessments and ongoing intelligence work, including sitting in front of clients.
What we're looking for:
- Essential:
- Real experience in social listening and online research, with one or more of the main tools (for example Brandwatch, Meltwater, Pulsar, Talkwalker, Sprinklr).
- Strong with both numbers and narrative. You can size a trend and read what is driving it.
- Genuinely digitally native. You understand how a story moves across X, Reddit, and Telegram into the mainstream, and how LLMs now shape what people believe.
- A confident, disciplined user of AI tools, with the judgement to know when an output is wrong. We need someone who treats AI as a fast junior, not an oracle.
- A clear writer. You can take something complicated and make it land in a sentence.
- Accurate and rigorous. You care whether the finding is actually true.
- Nice to have:
- Search, SEO, or GEO (AI visibility) experience.
- A background in corporate communications, public affairs, research, planning, or agency strategy.
- Experience in regulated or contested sectors (for example food and drink, energy, gambling, financial services, or government).
- Basic data visualisation, and comfort with polling or survey data.
How we will know it is working:
In your first six to twelve months we would expect you to be running PRISM's Conversation and Behaviour analysis with little oversight, to have tightened our classification method so outputs are consistent and defensible, and to have produced insight that changed what a client did. The measure is not how much you monitor. It is whether the work surprised someone and moved a decision.
Qualifications:
- Proficiency in All-Source Intelligence and Intelligence Analysis
- Strong Analytical Skills and expertise in interpreting qualitative and quantitative data
- Knowledge of Geospatial Intelligence and its practical applications
- Familiarity with the principles of National Security and its relevance to data analysis
- Comfort in handling large datasets and utilising AI-powered tools for insights
- Excellent communication skills, both written and verbal
- Ability to work collaboratively in an interdisciplinary and fast-paced environment
- Experience in strategy or data-driven campaign planning is a plus
- A bachelor's degree in Intelligence Studies, International Relations, Data Science, or a related field is preferred
Belief Intelligence Analyst employer: SPQR
SPQR is an exceptional employer, offering a dynamic work environment in the heart of Central London where innovation meets strategy. As a Belief Intelligence Analyst, you will have the opportunity to work with cutting-edge AI technology and collaborate with diverse teams, fostering both personal and professional growth. The company values rigorous analysis and clear communication, ensuring that your insights directly influence strategic decisions, making your role not just a job, but a meaningful contribution to shaping public opinion.
StudySmarter Expert Advice🤫
We think this is how you could land Belief Intelligence Analyst
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like SPQR!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Belief Intelligence Analyst at SPQR.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like SPQR.
✨Apply Directly through Our Website
When you find a suitable opening like Belief Intelligence Analyst at SPQR, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Belief Intelligence Analyst
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at SPQR, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at SPQR. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at SPQR
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at SPQR!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.