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Data Scientist

Qs · London, NW3 2DG, United Kingdom · Hybrid · Active · BambooHR

Job facts

FieldValue
CompanyQs
TitleData Scientist
Normalized title-
Department / teamData & Analytics
LocationLondon
Work modelHybrid / Hybrid
Employment typeFull Time
Salary-
Statusactive
ATS providerBambooHR
Posted / first seen2026-02-18 / 2026-05-30
Changed / last seen2026-05-30 / 2026-06-04

Related slices

PageWhat it containsOpen
Company jobsActive postings from Qs.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through BambooHR.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in London.Open
Department jobsActive postings in Data & Analytics.Open
Work model jobsActive Hybrid postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyQs
Sourcef2a0d97d-af95-4118-91ca-d9dc26e526ca
ATS providerBambooHR

Description

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. 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 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

Full job record

Job ID37ec4187e911219826de7b7d33af5b4bd07ba18d
Org IDc63c71b1-a112-41c0-937f-b9166b337f27
Source IDf2a0d97d-af95-4118-91ca-d9dc26e526ca
Board IDf2a0d97d-af95-4118-91ca-d9dc26e526ca
Providerbamboohr
Provider Job Key492
TitleData Scientist
Normalized Title
Statusactive
Activeyes
Location TextLondon, NW3 2DG, United Kingdom
DepartmentData & Analytics
Team
Employment Typefull_time
Workplace Typehybrid
Remote Policyhybrid
Country
Region
CityLondon
Salary Raw
Salary Min
Salary Max
Salary Currency
Salary Period
Source URLhttps://qs.bamboohr.com/careers/492
Apply URLhttps://qs.bamboohr.com/careers/492
First Seen At2026-05-30 06:10:53Z
Last Seen At2026-06-04 11:48:29Z
Last Checked At2026-06-04 11:48:29Z
Last Changed At2026-05-30 06:10:53Z
Inactive At
Source Posted At2026-02-18 00:00:00Z
Source Updated At
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Event Fields
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    "description": "<p><span style=\"font-weight: bold\">Role: Data Scientist</span></p>\n<p><span style=\"font-weight: bold\">Location: UK, London</span></p>\n<p><em>Applicants must have the existing right to work in the UK. This role is not eligible for visa sponsorship.</em></p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Job type: Full time, Permanent – Hybrid </span> </p>\n<p><em>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.</em></p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Why QS?</span></p>\n<p>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.</p>\n<p><br></p>\n<p>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.</p>\n<p><br></p>\n<p>Our diversity makes us stronger. By sharing our experiences, we learn from one another and achieve more together, driving progress across the sector.</p>\n<p> </p>\n<p>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.</p>\n<p> </p>\n<p>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.</p>\n<p> </p>\n<p><span style=\"font-weight: bold\">As a Data Scientist, this is what you’ll be doing:</span></p>\n<p>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.</p>\n<p><br></p>\n<p>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.<br></p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Role responsibilities</span></p>\n<p><span style=\"font-weight: bold\">Model Development</span></p>\n<ul>\n<li>Build and validate predictive, simulation and ranking-related models that inform global higher education and workforce insights.</li>\n<li>Develop models for student propensity, skills mobility, institutional performance and labour‑market trends.</li>\n<li>Engineer and transform structured, semi‑structured and longitudinal datasets into features suitable for production pipelines.</li>\n<li>Apply a range of statistical and machine‑learning techniques (e.g., gradient‑boosted models, graph methods, NLP, sequential simulation) to solve domain-specific problems.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Experimentation &amp; Analysis</span></p>\n<ul>\n<li>Design and run experiments to evaluate model performance and real‑world impact.</li>\n<li>Develop metrics frameworks to benchmark ranking methodologies and predictive systems.</li>\n<li>Communicate analytical findings clearly to technical and non‑technical stakeholders across the business.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Collaboration</span></p>\n<ul>\n<li>Work closely with Data Engineering to ensure modelling requirements are embedded into data pipelines and feature stores.</li>\n<li>Partner with Product and domain experts (rankings, labour‑market intelligence, student mobility) to ensure models align with business and sector needs.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Documentation &amp; Standards</span></p>\n<ul>\n<li>Document workflows, modelling decisions, assumptions and evaluation results.</li>\n<li>Contribute to shared modelling components, best practices and reusable analytical assets.</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Key skills and experience</span></p>\n<ul>\n<li>Proven experience in applied machine learning or data science.</li>\n<li>Proficiency in Python and SQL; experience with ML libraries such as scikit‑learn, LightGBM, TensorFlow, PyTorch, MLflow.</li>\n<li>Strong grounding in statistics, feature engineering and data wrangling.</li>\n<li>Familiarity with cloud platforms (AWS preferred) and Git.</li>\n<li>Ability to tackle ambiguous analytical problems and work collaboratively in cross-functional teams.</li>\n<li>Bachelor’s or Master’s degree in a quantitative field (Computer Science, Statistics, Mathematics or related).</li>\n</ul>\n<p> </p>\n<p><em>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.</em></p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">So, who are we and what do we do?</span></p>\n<p>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.</p>\n<p> </p>\n<p>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.</p>\n<p> </p>\n<p>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.</p>\n<p> </p>\n<p>Join QS and you’ll join an 800-strong community of problem-solvers, creators, collaborators and change-makers based in 40+ countries and 11<br>international offices, including Australia, Malaysia, India, Romania, Singapore, France, Germany, the USA and our headquarters in London.</p>\n<p> </p>\n<p>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?<br></p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">We take investing in our people very seriously.</span></p>\n<p>As standard you will have:</p>\n<ul>\n<li>Competitive base salary</li>\n<li>Access to an annual bonus scheme (for qualifying roles only)</li>\n<li>25 days annual leave, plus bank holidays – increasing to 27 days after 5 years’</li>\n<li>Access to a Buy Holiday scheme allowing you to buy up to 5 additional holiday days per year</li>\n<li>Enhanced maternity and paternity leave</li>\n<li>Generous pension through Royal London</li>\n<li>Comprehensive private medical insurance and wellness scheme through Vitality</li>\n<li>Cycle to work scheme</li>\n<li>A vibrant social environment and multicultural and multinational culture</li>\n</ul>\n<p> </p>\n<p>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:</p>\n<p><br></p>\n<ul>\n<li>Free subscription to the Calm App – the #1 app for sleep, meditation, and relaxation</li>\n<li>A focus on welfare which is led by our global wellness team, with mental health first aiders globally</li>\n<li>Access to a variety of diversity and inclusion initiatives and groups</li>\n<li>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</li>\n<li>Support for volunteering and study leave</li>\n<li>Free subscription to LinkedIn learning – with over 5000 courses and programmes at your fingertips</li>\n<li>Options to join our outstanding global Mentorship programme</li>\n</ul>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Like what you’ve heard? Great, apply now!</span></p>\n<p>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.</p>\n<p><br></p>\n<p><span style=\"font-weight: bold\">Equal opportunities </span></p>\n<p><em>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. </em></p>\n<p><br></p>\n<p>Please keep an eye on your spam / junk email folder for correspondence from BambooHR</p>\n<p><em> </em></p>\n<p><em> </em></p>",
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