Data Scientist
UK Visa Sponsorship Analytics
Above analytics are generated algorithmically based on job titles and may not always be the same as the company's job classification. You can also check detailed occupation eligibility, and salary criteria on our UK Visa Eligible Occupations & Salary Thresholds page.
Disclaimer: Hunt UK Visa Sponsors aggregates job listings from publicly available sources, such as search engines, to assist with your job hunting. We do not claim affiliation with QS Quacquarelli Symonds. For the most up-to-date job details, please visit the official website by clicking "Apply Now."
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 11international 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)
But that’s not all. Outside of these standard benefits we also offer resources to allow professional growth and wellness initiatives to nurture a healthy mindset:
- Free subscription to the Calm App – the #1 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
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