At a Glance
- Tasks: Lead data analysis and drive impactful changes in higher education rankings.
- Company: Join QS, a global leader in higher education analytics and insights.
- Benefits: Enjoy competitive salary, 25 days leave, wellness initiatives, and professional growth resources.
- Other info: Hybrid work model with vibrant multicultural environment and strong focus on employee wellbeing.
- Why this job: Make a real difference in the international education landscape with your analytical skills.
- Qualifications: Postgraduate degree in a quantitative field and proven data analytics experience required.
The predicted salary is between 60000 - 80000 £ per year.
Applicants must have the existing right to work in the UK. This role is not eligible for visa sponsorship. Job type: Full time, Permanent – Hybrid – 2 days in the office per week.
Why QS? At QS, it’s our mission to empower motivated people around the world to fulfil their potential through higher education, ensuring that everyone has access to opportunities that change lives. You’ll be responsible for implementing real change in the international higher education landscape. You’ll take on meaningful challenges that see a positive impact across the business and the wider sector.
As a Lead Data Analyst, this is what you’ll be doing:
- QS is looking for a Lead Data Analyst. This is a senior technical role at the heart of QS's rankings capability. You will take responsibility for the technical implementation, testing and production infrastructure, combining rigorous statistical and mathematical thinking with best-in-class data engineering and analysis to ensure our rankings remain the trusted source of higher education performance intelligence.
- This role will be internal and external facing. You will act as a senior technical representative, supporting external engagement by explaining and evidencing QS methodologies, engaging directly with senior institutional stakeholders, and building credibility with the academic and data‑science communities that scrutinise our methodology.
- Internally, you will drive methodological evolution, identifying where current approaches can be improved and ensuring adoption of more sophisticated statistical methods across data collection, production and analytical pipeline.
Methodology & Statistical Development
- Assess and evidence methodological changes using agreed evaluation criteria (e.g., stability, fairness, transparency, and susceptibility to data issues).
- Develop new analytical methods into the rankings production and downstream analysis pipeline.
- Develop and maintain rigorous sensitivity analyses and simulation frameworks to stress‑test ranking outputs against methodological and data‑quality interrogation.
- Stay at the forefront of the academic literature on composite indicators, university performance measurement, and data science, translating relevant advances into practical methodology improvements.
Rankings Data & Production
- Lead the technical aspects of the rankings production, working with data operations and engineering colleagues, ensuring the data pipelines, primarily in dbt (data build tool), are modular, tested, and implemented with version‑controlled transformation logic.
- Work closely with the data engineering team to align rankings data models with QS's broader Snowflake/AWS data lake architecture, ensuring rankings data is available to all internal stakeholders through the platform.
- Manage and mentor data analysts and engineers, elevating the team's technical standards and fostering professional growth.
- Enforce data quality frameworks, including automated validation, anomaly detection, and audit trails to ensure production‑grade reliability for all ranking inputs and outputs.
- Build reusable analytical tooling and notebooks that allow the wider Rankings team to interrogate outputs, run what‑if scenarios, and conduct deep‑dives without requiring bespoke engineering support.
- Maintain comprehensive technical documentation of methodology, transformation logic, and production processes to support governance, audit, and external transparency.
External Engagement & Client Facing Work
- Represent QS rankings at international conferences, academic forums, and industry events, presenting statistical and technical content to expert audiences with clarity and authority.
- Act as the primary technical point of contact for universities, government bodies, and research institutions seeking to understand or engage with rankings methodology at a deep level.
- Balance transparency with protection of proprietary methods, producing alongside product stakeholder‑friendly explanations without exposing implementation details.
- Develop high‑quality technical papers, methodology notes, and white papers that strengthen QS's credibility and thought leadership in the global rankings and higher education intelligence space.
- Collaborate with the Commercial, Product and Consulting teams to ensure that rankings insights and derivative analytical products are communicated in ways that resonate with both technical and non‑technical client audiences.
Analytics & Insight
- Design and deliver advanced downstream analyses and thought leadership built on rankings data, using AI tools to build automation into the production of these analyses.
- Drive the improvement of the team's data storytelling by transforming complex analytical findings into compelling, high‑impact visual narratives and presentations that influence decision‑making and set a new gold standard for design excellence across the organisation.
- Develop scenario and explanatory models that surface the drivers of ranking performance, enabling institution and governmental strategic planning.
- Partner with Content, Marketing and our various Insights teams to integrate rankings data with QS's broader assets (labour market data, student flows, etc.) into compelling, multi‑dimensional analyses, using AI tools to automate the dissemination of these datasets and analyses across non‑technical teams.
- Contribute to the development of new QS frameworks, including the World Future Skills Index by bringing quantitative rigour to indicator design and output validation.
Key skills and experience
Must Have
- Postgraduate degree in Mathematics, Statistics, Econometrics, Data Science, or a closely related quantitative discipline from a leading university.
- Clear evidence of organisational impact, leadership and driving transformation across legacy business and data operations.
- Proven experience in data analytics, or a proven accelerated career trajectory demonstrating readiness for a lead‑level role.
- Demonstrable expertise in applied statistics: multivariate analysis, composite indicator construction, normalisation methodologies, regression modelling, and uncertainty quantification.
- Strong proficiency in SQL.
- Proficiency in Python for statistical analysis, simulation, and model development.
- Experience working with large, complex, multi‑source datasets in a production analytical environment.
- Ability to present technical and statistical content confidently to non‑specialist audiences, including clients, senior leadership, and conference delegates.
- Exceptional story‑telling and presentation design skills.
- Strong written communication skills, including the ability to produce rigorous methodology documentation and stakeholder‑facing technical papers.
- A demonstrated instinct for methodological scrutiny, ability to identify weaknesses in existing approaches and propose well‑evidenced improvements.
Nice to Have
- Familiarity with higher education data, university performance metrics, or rankings methodology.
- Knowledge of Snowflake, AWS, or similar modern cloud data platform architectures.
- Experience with dbt (data build tool) for building modular, tested transformation pipelines in a cloud data warehouse environment (Snowflake or equivalent) is an advantage.
- Experience building or contributing to published composite indices or benchmarking frameworks.
- Track record of presenting at or publishing in academic or professional forums related to data science, statistics, or education research.
- Experience working in a cross‑functional product or data platform environment.
Please note, if you don't meet all the criteria but believe you have the skills and passion to thrive in this role, we encourage you to apply.
So, who are we and what do we do? QS is the world leader in higher education services, analytics, insights and intelligence. From consultancy to student mobility, academic partnerships to branding solutions, our services power both institutional and individual success. We’re behind the world’s most widely read university rankings (Meltwater 2023). Our QS World University Rankings® reach hundreds of millions, shaping decisions and guiding futures.
We take investing in our people very seriously. As standard you will have:
- Access to an annual bonus scheme (for qualifying roles only).
- 25 days annual leave, plus bank holidays – increasing to 27 days after 5 years’.
- Access to a Buy Holiday scheme allowing you to buy up to 5 additional holiday days per year.
- Enhanced maternity and paternity leave.
- Generous pension through Royal London.
- Comprehensive private medical insurance and wellness scheme through Vitality.
- Cycle to work scheme.
- A vibrant social environment and multicultural and multinational culture.
But that’s not all. Outside of these standard benefits we also offer resources to allow professional growth and wellness initiatives to nurture a healthy mindset:
- Free subscription to the Calm App – the #1 app for sleep, meditation, and relaxation.
- A focus on welfare which is led by our global wellness team, with mental health first aiders globally.
- Access to a variety of diversity and inclusion initiatives and groups.
- Strong recognition and reward programs – including a peer‑to‑peer recognition platform, quarterly and annual QS Applaud Awards, Connect with your Career annual PD event.
- Support for volunteering and study leave.
- Free subscription to LinkedIn learning – with over 5000 courses and programmes at your fingertips.
- Options to join our outstanding global Mentorship programme.
Like what you’ve heard? Great, apply now!
Equal opportunities
QS Quacquarelli Symonds is proud to be a fair and equal organisation where everyone has the same opportunity to achieve their full potential, irrespective of their background or personal attributes. We celebrate our diversity and believe through sharing our experiences we can learn from one another, be stronger together, and enable our business to thrive.
Lead Data Analyst (Rankings) employer: QS Quacquarelli Symonds
At QS, we are committed to fostering a vibrant and inclusive work culture that empowers our employees to thrive. As a Lead Data Analyst, you will not only engage in meaningful work that shapes the future of higher education but also benefit from a comprehensive range of perks including generous annual leave, professional development opportunities, and wellness initiatives. Our hybrid working model allows for flexibility while being part of a dynamic team dedicated to making a positive impact globally.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Analyst (Rankings)
✨Tip Number 1
Network like a pro! Reach out to current or former QS employees on LinkedIn. A friendly chat can give you insider info and maybe even a referral. Remember, it’s all about who you know!
✨Tip Number 2
Prepare for the interview by diving deep into QS's methodologies and recent projects. Show us you’re not just another candidate; demonstrate your passion for higher education and how you can contribute to our mission.
✨Tip Number 3
Practice your storytelling skills! When discussing your experience, frame it in a way that highlights your impact and leadership. We want to see how you’ve driven transformation in past roles.
✨Tip Number 4
Don’t forget to follow up after your interview! A quick thank-you email reiterating your enthusiasm for the role can leave a lasting impression. It shows us you’re genuinely interested in joining the QS team.
We think you need these skills to ace Lead Data Analyst (Rankings)
Some tips for your application 🫡
Tailor Your Application:Make sure to customise your CV and cover letter for the Lead Data Analyst role. Highlight your relevant experience in data analytics, statistical methods, and any leadership roles you've held. We want to see how you can make an impact at QS!
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples from your past work that showcase your expertise in SQL, Python, and applied statistics. We love seeing how you’ve used these skills to drive transformation.
Be Clear and Concise:When writing your application, keep it clear and to the point. Avoid jargon unless necessary, and make sure your passion for higher education and data analysis shines through. We appreciate straightforward communication!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, you’ll find all the details you need about the role and our company culture there!
How to prepare for a job interview at QS Quacquarelli Symonds
✨Know Your Stats
As a Lead Data Analyst, you'll need to showcase your expertise in applied statistics. Brush up on multivariate analysis, regression modelling, and uncertainty quantification. Be ready to discuss how you've used these skills in past projects, as this will demonstrate your capability to drive methodological evolution at QS.
✨Showcase Your Technical Skills
Make sure you can confidently talk about your proficiency in SQL and Python. Prepare examples of how you've worked with large datasets and built modular transformation pipelines using dbt. This will highlight your readiness for the technical aspects of the role and your ability to manage data quality frameworks.
✨Engage with the Audience
You'll be presenting to both technical and non-technical audiences, so practice explaining complex concepts in simple terms. Think about how you can make your statistical content engaging and relatable. This skill will be crucial when representing QS at conferences or engaging with institutional stakeholders.
✨Prepare for Methodological Scrutiny
Expect questions about your approach to methodological changes and how you assess their impact. Be prepared to discuss any weaknesses you've identified in existing methods and how you've proposed improvements. This will show your instinct for methodological scrutiny and your commitment to maintaining QS's credibility.