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About the Role

This is a senior technical role at the heart of QS's rankings capability, responsible for technical implementation, testing, and production infrastructure. It combines statistical and mathematical thinking with data engineering and analysis to ensure rankings remain a trusted source of higher education performance intelligence. The role is both internal and external facing, acting as a senior technical representative for methodology explanations, engaging with stakeholders, and driving methodological evolution internally.

Responsibilities

Assess and evidence methodological changes using agreed evaluation criteria.
Develop new analytical methods into the rankings production and downstream analysis pipeline.
Develop and maintain rigorous sensitivity analyses and simulation frameworks.
Translate relevant advances in composite indicators, university performance measurement, and data science into practical methodology improvements.
Lead the technical aspects of rankings production, ensuring data pipelines are modular, tested, and implemented with version-controlled transformation logic.
Align rankings data models with QS's broader Snowflake/AWS data lake architecture.
Manage and mentor data analysts and engineers, elevating technical standards and fostering professional growth.
Enforce data quality frameworks, including automated validation, anomaly detection, and audit trails.
Build reusable analytical tooling and notebooks for the Rankings team.
Maintain comprehensive technical documentation of methodology, transformation logic, and production processes.
Represent QS rankings at international conferences, academic forums, and industry events.
Act as the primary technical point of contact for universities, government bodies, and research institutions.
Balance transparency with protection of proprietary methods, producing stakeholder-friendly explanations.
Develop high-quality technical papers, methodology notes, and white papers.
Collaborate with Commercial, Product, and Consulting teams to communicate rankings insights.
Design and deliver advanced downstream analyses and thought leadership built on rankings data, using AI tools for automation.
Drive the improvement of the team’s data storytelling by transforming complex analytical findings into compelling visual narratives.
Develop scenario and explanatory models to surface the drivers of ranking performance.
Partner with Content, Marketing, and Insights teams to integrate rankings data with QS's broader assets.
Contribute to the development of new QS frameworks, including the World Future Skills Index.

Requirements

Must have the existing right to work in the UK.
Postgraduate degree in Mathematics, Statistics, Econometrics, Data Science, or a closely related quantitative discipline from a leading university.
Clear evidence of organizational 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.
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.

Skills

dbt (data build tool)
Snowflake
AWS
Python
SQL
AI tools

Location

UK, London

Work Type

Full time
Permanent
Hybrid

Experience Level

Lead-level
Senior technical role

Education Level

Postgraduate degree in Mathematics, Statistics, Econometrics, Data Science, or a closely related quantitative discipline

Benefits

Competitive base salary
Access to an annual bonus scheme
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
Free subscription to the Calm App
Focus on welfare led by a 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
Support for volunteering and study leave
Free subscription to LinkedIn learning

About the Company

QS is the world leader in higher education services, analytics, insights and intelligence.
We are behind the world’s most widely read university rankings.
We work with more than 2,000 of the world’s leading higher education institutions, over 12,000 employers, and governments.
QS was named as one of Newsweek’s Top 100 Most Loved Workplaces® in the UK (October 2023).
QS is a gold-accredited Investors in People organisation.

Equal Opportunity

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.