Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Senior Data Scientist, Recommendations

Bumble Inc.
London
11 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist

Senior Data Scientist, Generative AI Innovation Center, AWS Generative AI Innovation Center

Bumble is looking for a Senior Data Scientist to join our team and play a key role in fulfilling our mission to create a world where all relationships are healthy and equitable. Concretely, this means exploring our large datasets, developing statistical models and designing data-driven strategies for products that provide a safe and engaging experience for our users, and improve the way Bumble operates.

Interested in learning more about this job Scroll down and find out what skills, experience and educational qualifications are needed.

With millions of images and messages exchanged on our platform every day, there is a wealth of opportunity to make a real difference in this role and help people find love all over the world! The ideal candidate combines strong business acumen, extensive experience in data science and advanced analytics along with a passion for tech.

THE RECOMMENDATIONS TEAM

We are part of the cross-functional Recommendations group at Bumble Inc., a team of passionate engineers, scientists, and machine learning professionals who focus on designing and building products that power our mission of "creating a world where all relationships are healthy and equitable, through Kind Connections." We partner with wider business stakeholders, Product, and other Engineering teams to build state-of-the-art recommendation systems for our portfolio of apps, including Bumble, Badoo, BFF, and Fruitz. We are passionate about improving the experience of our members through leveraging AI and Machine Learning in our products.

WHAT YOU WILL BE DOING

Work in a cross-functional team alongside machine learning scientists and machine learning engineersWork out where the most value is and help set up frameworks for evaluating algorithmic improvementsSet up and conduct large-scale experiments to test hypotheses and drive product developmentAssess impact of algorithm changes on marketplace dynamicsPartner with business functions and engineering teams to help frame problems into scalable AI solutions and solve key problems by leveraging the large and complex datasets at our disposalCollaborate with Product Management to establish roadmaps and define key metrics to optimise for alignment with Bumble's strategic objectivesDrive a culture of insightful storytelling across the businessKeep up with state-of-the-art research with the opportunity to create prototypes for the business and present at top conferences>WE'D LOVE TO MEET SOMEONE WITHA degree in Computer Science, Mathematics or a similar quantitative discipline like economics or social scienceStrong statistical modelling background - hypotheses testing, inference, regressions, random variablesComfortable presenting back to technical and non-technical stakeholders through effective data visualisation and building of reporting frameworksComfortable with Python data science libraries such as pandas, scikit-learn, numpy, statsmodelsStrong SQL experience including analytic functions, performance tuning, data wranglingAbility to work collaboratively and proactively in a fast-paced environment alongside scientists, engineers and non-technical stakeholdersAbility to combine business intuition with the application of advanced solutionsA passion for keeping up with the latest ongoings in Data Science and Machine Learning communitiesA curious mind, self-starter and endlessly keen to learn and develop themselves professionally

AN ADDED BONUS IF YOU HAVEAn understanding of multi-sided markets and/or dating problem spaceExperience in using advanced statistical methods to solve problems. This can either be through academic projects and publications, or experience analysing and solving problems within industryUnderstanding of Machine Learning development lifecycleHands-on experience in delivering Machine Learning modelsA basic knowledge of software development life cycle processes and tools - ETL pipelines, CI/CD, MLOps, agile methodologies, version control (git), testing frameworks>

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.