Quacquarelli Symonds Limited

Role: 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. Why QS? At QS, we believe that work should empower you. That's 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. 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. Our diversity makes us stronger. By sharing our experiences, we learn from one another and achieve more together, driving progress across the sector. 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. We're confident you'll feel right at home here. QS was named as one of Newsweek's Top 100 Most Loved Workplaces in the UK (October 2023), recognising the respect, trust and appreciation that drive our culture every day. And as a gold-accredited Investors in People organisation - putting us among the top 28% of workplaces globally - it's official: QS is a place where everyone can thrive. As a Data Scientist, this is what you'll be doing: 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. You'll 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. Role responsibilities Model Development 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. Experimentation & Analysis 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. Collaboration 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. Documentation & Standards Document workflows, modelling decisions, assumptions and evaluation results. Contribute to shared modelling components, best practices and reusable analytical assets. Key skills and experience 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). 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. So, who are we and what do we do? 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. With every talented new hire, business acquisition and bold initiative, we're strengthening our reach and delivering even greater value to institutions and learners worldwide. Are you ready to shape the future of higher education? We take investing in our people very seriously. 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 A vibrant social environment and multicultural and multinational culture But that's not all. Free subscription to the Calm App - the 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 Like what you've heard? Great, apply now! As a candidate, we know the application and interview process can be daunting and so it's important that you have a great experience with us. Our dedicated Talent Team will work hard to ensure you are fully informed at all stages and you are really excited by this opportunity to do meaningful work in the education space. 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. Please keep an eye on your spam / junk email folder for correspondence from BambooHR

A leader in higher education services is seeking a Data Scientist to develop predictive models and contribute to impactful analytical projects. The role offers a hybrid work model, allowing for flexibility with two days in the office per week. The successful candidate will collaborate with teams to build robust solutions and take on challenges that influence higher education worldwide. Strong proficiency in Python, SQL, and machine learning is essential for this position.