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Data Scientist, Trust & Safety

bumbleinc · 30+ days ago
Negotiable
Full-time
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Bumble is looking for a 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 billions of collected data points and 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 to find love all over the world! The ideal candidate combines strong business acumen, extensive experience in data science and advanced analytics along with a background in trust & safety.

Trust & Safety
We are part of the Trust & Safety Engineering group, a cross-functional team of 40+  engineers, scientists and machine learning professionals that help grow kind, healthy & equitable connections by designing and operationalizing the safest and most trusted connections platform in the industry.  We partner with the wider business to create and share tooling, knowledge, and best practices around Trust and Safety technology while undertaking special product and development initiatives designed to improve the actual safety and felt experience of safety of members across our products. We’re known by the wider industry as experts in our field, and give back to the community through thought leadership, information sharing, and open-sourcing.

WHAT YOU WILL BE DOING

  • Work in a cross-functional team alongside data scientists and machine learning engineers.
  • Analyse large sets of data and work closely with Safety Product Management to educate roadmaps and define key metrics, aligning them with Bumble Inc's goals.
  • Identify areas of maximum value and contribute to setting up frameworks for evaluating algorithmic improvements. 
  • Initiate and conduct large-scale experiments to test hypotheses and drive product development.
  • Partner effectively with business functions and engineering teams to translate problems into scalable AI solutions, leveraging the richness of our extensive and intricate datasets.
  • Foster a culture of insightful storytelling across our Group and the business, emphasising collaboration and connection within the team. Your style is characterised by empathy, open communication, and a commitment to promoting diversity and inclusion.

WE’D LOVE TO MEET SOMEONE WITH

  • 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

  • A proven background in trust & safety or experience of working in a similar role.
  • 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
  • A basic knowledge of software development life cycle processes and tools - ETL pipelines, CI/CD, MLOps, agile methodologies, version control (git), testing frameworks 

Last updated on Oct 15, 2024

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