Data Science Specialist leading predictive modeling initiatives to support product innovation at Nestlé Nutrition. Collaborating with cross - functional teams to translate complex data into actionable insights.
About the role
- 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
Job title
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