Senior Data Scientist - Forecasting

Job description

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 where you will tackle a wide range of strategic tasks directly for the Bumble leadership team. Together with us you will contribute to our business forecasting implementation, perform scenario modelling, metrics innovation, segmentation and apply visualisation know-how.

If you want to work with some of the most exciting technologies for big data, this is your chance! We constantly review and extend our tool stack to remain current. Continuous learning is a crucial part of the job. If you are passionate about the dating market or about our products and if any of the above speaks to you, we would like to hear from you!


  • Deliver impactful results through the development of our current forecasting capabilities

  • Iterate on our scenario modelling and what-if solutions and further drive decision sciences capabilities

  • Pick up and own a variety of strategic tracks on a range of topics (e.g. impact of a post-covid world on dating, how will certain new markets respond to Bumble entry), perform data analyses and translate finding to actionable business implications

  • Take the lead on new exploratory or innovation research projects in a wide variety of areas

  • Partner with the wider Business Analytics and data sciences teams to solve bigger business problems

  • Drive a culture of insightful storytelling across the Business Analytics team and beyond.


  • Proven experience with a range of time series methodologies and frameworks such as arima, ets, prophet and neural nets

  • A clear understanding of the pros, cons and correct domain of application of the main different forecasting methods

  • Strong statistical modelling background

  • Demonstrable experience implementing machine learning models; from initial conception right through to the final productionalised model

  • Confident in terms of programming and scripting (strong Python essential)

  • Comfortable working directly and indirectly with C-suite business leaders and strategy stakeholders

  • Experience in presenting findings to varying audiences (technical and non-technical stakeholders) and catering presentation style appropriately

  • Good SQL knowledge: you’ll know how to join/union data and are skilled with analytic functions and you’re autonomous in prepping your own datasets


  • Working knowledge of design thinking & agile methodologies

  • Comfortable with visualizing data in a range of output formats (e.g. decks) or tools (e.g. BI tools such as Tableau, Microstrategy etc.) with clear attention to storytelling

  • Excellent attention to detail and a clear and concise writing style

  • Comfortable working with a broad range of BI tools (or willingness to pick up new tools quickly), identifying the most appropriate solutions across diverse stakeholder needs

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