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Splice is a creative platform for music producers offering a subscription service with sounds, samples, and an expanding AI stack, plus a rent-to-own marketplace for DAWs and plugins. The company operates with a remote-first culture across the US and UK.
As Staff Data Analyst, you will be a central figure in shaping Splice's future by ensuring data-driven decision-making across the organization. You'll join the centralized analytics team supporting product analytics, marketing analytics, and business operations, working as a key collaborator in modernizing the data stack for an AI-first world. This is a highly visible cross-functional role alternating between executive leadership and engineering teams.
Key responsibilities include:
- Building and maintaining data models that drive valuable insights and support critical workflows
- Translating complex questions into actionable metrics across Product, Marketing, Audio Development, and other teams
- Partnering with Product and Marketing on user activation funnels, drop-off analysis, and A/B test design/interpretation
- Creating and managing self-serve reporting tools and dashboards via Omni to track growth KPIs and product health
- Optimizing and tracking data stack components (Omni, Hex, Segment), driving adoption and proposing alternatives
- Delivering ad hoc data-driven insights to leadership, product, and marketing stakeholders
Required qualifications: 10+ years in Data Analytics or similar roles; demonstrated BI platform experience (Omni, Looker, Tableau, PowerBI, Qlik) including semantic layers; strong statistical knowledge (trend analysis, hypothesis testing, confidence intervals); advanced SQL (CTEs, ELT vs ETL, query optimization); basic Python or R proficiency; prior product or marketing organization experience; enterprise data solutions experience with tools like Segment, Amplitude, LaunchDarkly, BigQuery, SQLMesh, and Fivetran.
Nice-to-haves include Bayesian Inference knowledge, data team roadmap management experience, company-level KPI setting, music industry background, AI workflow improvements, marketing analytics toolkit experience, and Data Engineering collaboration.
