Data Scientist developing predictive models and data pipelines to enhance global higher education insights. Collaborating with teams to apply machine learning techniques and contribute to important analytical projects.
Responsibilities
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
Apply a range of statistical and machine‑learning techniques (e.g., gradient‑boosted models, graph methods, NLP, sequential simulation) to solve domain-specific problems
Design and run experiments to evaluate model performance and real‑world impact
Develop metrics frameworks to benchmark ranking methodologies and predictive systems
Communicate analytical findings clearly to technical and non‑technical stakeholders across the business
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
Requirements
Proven experience in applied machine learning or data science
Proficiency in Python and SQL; experience with ML libraries such as scikit‑learn, LightGBM, TensorFlow, 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
Bachelor’s or Master’s degree in a quantitative field (Computer Science, Statistics, Mathematics or related)
Benefits
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
A vibrant social environment and multicultural and multinational culture
Free subscription to the Calm App – the #1 app for sleep, meditation, and relaxation
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
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