QS Quacquarelli Symonds
Lead Data Analyst (Rankings)
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Role: Lead Data Analyst (Rankings)
Location: UK, London
Job type: Full time, Permanent – Hybrid - 2 days in the office per week.
Applicants must have the existing right to work in the UK. This role is not eligible for visa sponsorship.
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.
At QS, 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.
Role Overview
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.
Role Responsibilities
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.
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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.
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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.
About Us
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.
Benefits
As standard you will have:
- Competitive base salary
- 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
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
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.
Like what you’ve heard? Great, apply now!
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