Data Scientist

Location:

UK, London

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

This position offers a hybrid work model, allowing flexibility between working from home and our office. Typically, employees are expected to work 2 days in the office per week.

At QS, we believe that work should empower you. Thats why we foster a flexible working environment that encourages every employee to own their career whilst flourishing personally and professionally. Our company values underpin everything we do: we collaborate, respect and support each other.

Location:

UK, London

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

This position offers a hybrid work model, allowing flexibility between working from home and our office. Typically, employees are expected to work 2 days in the office per week.

As a Data Scientist, you will work on high-impact analytical and modelling projects that sit at the core of QS's mission to improve higher education worldwide. You will develop models and pipelines that power university ranking simulations, track global skill movements, and predict student behaviour at scale.

Youll collaborate closely with senior data scientists, engineers, and product teams, using QS's rich global datasets to build robust, production-grade solutions. This role is ideal for someone who wants to deepen their technical expertise while contributing to work that influences institutions, learners, and policymakers around the world.

• Build and validate predictive, simulation and ranking-related models that inform global higher education and workforce insights.
• Develop models for student propensity, skills mobility, institutional performance and labour-market trends.
• Engineer and transform structured, semi-structured and longitudinal datasets into features suitable for production pipelines.

• Design and run experiments to evaluate model performance and real-world impact.
• Develop metrics frameworks to benchmark ranking methodologies and predictive systems.

• Work closely with Data Engineering to ensure modelling requirements are embedded into data pipelines and feature stores.
• Partner with Product and domain experts (rankings, labour-market intelligence, student mobility) to ensure models align with business and sector needs.

• Document workflows, modelling decisions, assumptions and evaluation results.
• Contribute to shared modelling components, best practices and reusable analytical assets.

• Proven experience in applied machine learning or data science.
• Proficiency in Python and SQL; experience with ML libraries such as scikit-learn, Light
  
  GBM, Tensor Flow, PyTorch, MLflow.
• Strong grounding in statistics, feature engineering and data wrangling.
• Familiarity with cloud platforms (AWS preferred) and Git.
• Ability to tackle ambiguous analytical problems and work collaboratively in cross-functional teams.

Bachelors or Masters degree in a quantitative field (Computer Science, Statistics, Mathematics or related).

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.

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.

Since launching in 1990, our impact and influence have only grown. Today, we work with more than 2,000 of the world's leading higher education institutions, over 12,000 employers, and governments seeking change and socioeconomic development through higher education.

Join QS and you'll join an 800-strong community of problem-solvers, creators, collaborators and change-makers based in 40+ countries and 11 international offices, including Australia, Malaysia, India, Romania, Singapore, France, Germany, the USA and our headquarters in London.

• 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

• Free subscription to the Calm App the #1 app for sleep, meditation, and relaxation
• A…