Senior Data Scientist, Recommendations

Job title:

Senior Data Scientist, Recommendations

Company

Bumble Inc.

Job description

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.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 TEAMWe 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 engineers
• Work out where the most value is and help set up frameworks for evaluating algorithmic improvements
• Set up and conduct large-scale experiments to test hypotheses and drive product development
• Assess impact of algorithm changes on marketplace dynamics
• Partner 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 disposal
• Collaborate with Product Management to establish roadmaps and define key metrics to optimise for alignment with Bumble’s strategic objectives
• Drive a culture of insightful storytelling across the business
• Keep 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 WITH

• A degree in Computer Science, Mathematics or a similar quantitative discipline like economics or social science
• Strong statistical modelling background – hypotheses testing, inference, regressions, random variables
• Comfortable presenting back to technical and non-technical stakeholders through effective data visualisation and building of reporting frameworks
• Comfortable with Python data science libraries such as pandas, scikit-learn, numpy, statsmodels
• Strong SQL experience including analytic functions, performance tuning, data wrangling
• Ability to work collaboratively and proactively in a fast-paced environment alongside scientists, engineers and non-technical stakeholders
• Ability to combine business intuition with the application of advanced solutions
• A passion for keeping up with the latest ongoings in Data Science and Machine Learning communities
• A curious mind, self-starter and endlessly keen to learn and develop themselves professionally

AN ADDED BONUS IF YOU HAVE

• An understanding of multi-sided markets and/or dating problem space
• Experience in using advanced statistical methods to solve problems. This can either be through academic projects and publications, or experience analysing and solving problems within industry
• Understanding of Machine Learning development lifecycle
• Hands-on experience in delivering Machine Learning models
• A basic knowledge of software development life cycle processes and tools – ETL pipelines, CI/CD, MLOps, agile methodologies, version control (git), testing frameworks

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Expected salary

Location

London

Job date

Thu, 24 Oct 2024 22:55:33 GMT

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