Associate Data Analyst, Revenue

August 8

🔄 Hybrid – London

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Logo of Bumble Inc.

Bumble Inc.

Our mission is to create a world where all relationships are healthy and equitable, through Kind Connections.

501 - 1000

Description

• You’ll have access to the most diverse, varied and complex data sets in the technology world right now (10’s of billions of data points per day!!) • You’ll be doing all the typical day-to-day tasks such as generating practical insights from the data, manipulating complex datasets, helping us understand how to improve and optimise our members experience to facilitate the creation of meaningful, equitable and healthy relationships • Unlock your potential by upskilling in SQL, Python and other essential tools, empowering you to expand your skill set and excel in your career • You will help uncover tactical and strategic insights and support experimentation in a range of areas such as revenue management, operations and strategy. For instance, you could work on testing and validating pricing and promotion based opportunities across our portfolio of apps. • You will make contributions to the data model and could contribute to building out data pipelines • You’ll collaborate closely with several potential teams including Product Managers, strategists, operations managers, and Data Engineers PLUS, you’ll be building detailed, entrepreneurial and business-minded insights that directly contribute to the successful growth of Bumble Inc.

Requirements

• Supporting experimentation analytics (e.g. A/B testing, user group testing): significance analysis, non-parametric methods, bootstrapping, causal inference • Manipulating complex datasets using a range of tools such as SQL and Hive • Building effective self serve tools and visualisations to help optimise decision making • Engaging and collaborating with key stakeholders such as developers, product managers, and senior management • Identifying issues and opportunities, translating business problems into analytical diagnoses and delivering insights that answer the most pressing questions • Supporting engineers and teammates in improving data quality, and specifying requirements for new data collection • Partnering with the wider analytics / data science team to solve business problems • Experience in Python is desirable but not required • Experience with data modelling and make domain-specific data models is a plus

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