Senior Data Scientist - Recommendations

Full time

Employment Information

We strongly encourage people of colour, lesbian, gay, bisexual, transgender, queer and non-binary people, veterans, parents, and individuals with disabilities to apply. Bumble is an equal opportunity employer and welcomes everyone to our team. If you need reasonable adjustments at any point in the application or interview process, please let us know.

In your application, please feel free to note which pronouns you use (For example - she/her/hers, he/him/his, they/them/theirs, etc).

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 team

We are part of the cross-functional Recommendations group at Bumble Inc., a team of 20+ 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’ll be doing

  • Work in a cross-functional team alongside machine learning scientists and machine learning engineers
  • Working out where the most value is and helping set up frameworks for evaluating algorithmic improvements
  • Set up and conduct large-scale experiments to test hypotheses and drive product development
  • 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 publish 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, statsmodel
  • 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

  • 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
  • Experience using deep learning libraries like TensorFlow/Keras or PyTorch
  • An understanding of multi-sided markets and/or dating problem space
  • 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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