Bumble Inc.
Our mission is to create a world where all relationships are healthy and equitable, through Kind Connections.
501 - 1000
Senior Data Scientist, Revenue
4 days ago
🔄 Hybrid – London
Bumble Inc.
Our mission is to create a world where all relationships are healthy and equitable, through Kind Connections.
501 - 1000
Description
• Lead the development of advanced CLV models tailored to the unique dynamics of our two-sided marketplace, leveraging complex sources of revenue, payments, and behavioral data. • Collaborate closely with stakeholders and senior leaders to identify key business problems, challenge priorities, and provide actionable insights derived from CLV modeling. • Guide others on techniques and ways of working and help build a culture of critical thinking, commercial acumen and disciplined execution in alignment with senior management. • Drive data science roadmaps by efficiently producing insights that inform decision-making, supporting an extensive experimentation program, and advocating for continual improvement within the team. • Take an integrated perspective to analytics, considering all potential drivers to a problem, reviewing existing knowledge, and leveraging expertise from other teams to enhance the effectiveness of CLV modelling efforts.
Requirements
• Preference for a graduate degree in Mathematics, Engineering, Information Sciences, Economics, Finance, or STEM. • Preference for experience working in similar dating/social/gaming tech product industries or else financial services/high-data-volume industries. • Proven experience in building and deploying ML and statistical models for demand forecasting, segmentation, and CLV estimation. • 3+ years of experience with python/SQL, machine learning/data science tooling such as Kubeflow/Streamlit and visualisation tooling such as Looker/Tableau. • Strong understanding of machine learning applications development life cycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps, agile methodologies, monitoring and alerting. • Experience working with complex data infrastructures and have experience partnering and guiding the work of data engineering to help facilitate ingestion, warehousing, and optimisation of databases. • Strong experience with data engineering and data modelling requirements needed to automate reporting and measurement.
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