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Über
A fast-growing
social and content platform
is looking to bring on
1-2 experienced Staff Data Scientists
to help rebuild and strengthen its data science capability. This role will work closely with product leadership to drive key company metrics and help shape the growth of the platform's social ecosystem.
The Role
You will partner closely with Product Managers and engineering teams to analyse user behaviour across the platform's social graph and develop data-driven strategies to support creator and host growth. A key focus will be identifying opportunities to help users expand their hosting networks and drive engagement and revenue.
The team operates in a
fully remote, low-meeting environment , so strong asynchronous communication and the ability to operate independently are essential.
Key Responsibilities Own and drive key company metrics related to platform engagement and growth Partner closely with Product Managers to identify and prioritise data-driven opportunities Analyse and model
social graph dynamics
to understand user interaction patterns Design and run
A/B tests
to optimise product experiences Develop
next-best-experience recommendations
to improve user outcomes Contribute to and maintain an existing
Python-based data science codebase Support internal data engineering workflows where required Deliver meaningful insights and deep-dive analyses within the first month of onboarding Requirements
Proven
Staff-level Data Scientist experience Very strong SQL
skills Strong Python expertise
in production environments Experience with
large-scale experimentation / A/B testing Ability to work with large datasets and social interaction data Clear, proactive communicator who thrives in asynchronous environments Experience working closely with product teams on growth initiatives Comfortable operating with high expectations and fast onboarding Nice to Have
Experience working with
social platforms, community products, or consumer marketplaces Familiarity with
social graph analysis Experience with
Django Experience supporting or collaborating with
data engineering teams Background working in fast-moving or "scrappy" product environments Working Environment
Fully remote team Flexible on timezone, but availability relative to
PST working hours
should be communicated upfront
Sprachkenntnisse
- English
Hinweis für Nutzer
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