Job Description

TIDAL is looking for a Marketing Analyst to join the Global Marketing team to support TIDAL’s Marketing organization in their pursuit of building a globally loved brand and bringing the next generation of artists and fans to TIDAL.

You will provide analytical support for our Global Marketing team, driving reporting of our paid media efforts and growing visibility with our company on the contribution and value of those efforts on bottom-line business growth. Success will require gaining a comprehensive understanding of TIDAL’s Performance Marketing and Paid Media strategy, providing clear insights and trends, and developing a trusted partnership with partners.

This remote friendly role reports into the Global Strategy and Insights Lead and involves cross-functional collaboration. You’ll have direct access to a growing team of other analysts and data engineers to deliver on work required, help inform the build of new data pipelines, and continue to hone and grow your analytics. #LI-Remote

You Will:

• Be the team’s subject matter expert on paid media analytics - including reporting, media effectiveness insights, data standards and hygiene
• Build comprehensive measurement plan on how to best evaluate paid media performance based on specific marketing objectives, and use data to make recommendations on optimization
• Build, validate and deploy media mix models, modeling and attribution model solutions to help improve our marketing measurement
• Define and standardize methodology for measuring, forecasting and reporting on media campaign effectiveness globally including Return on investment, lifetime value, messaging impact, benchmarks, incrementality, and brand lift metrics at the channel.
• Help guide automation and reporting solutions through collaboration with business partners, Finance & Strategy, and/or Business Intelligence & Engineering teams
• Analyze large sets of data, distilling them into actionable insights and trends to help the Global Brand and Performance Marketing team improve the effectiveness and efficiency of their investments to achieve their goals
• Leverage existing tools to help facilitate and build the narratives around quarterly forecasts and changes when comparing investments Year-over-year and QoQ
• Act as the bridge between business teams and technical teams to gather system and data requirements
• Create data visualizations to provide greater transparency for our stakeholders at the regional and/or market level where possible
• Report efficiency of ad hoc campaigns and their impact to evergreen initiatives
• Partner cross functionally with other analysts, data scientists, and data engineers to build and maintain data pipelines, processes, and reporting solutions/visualizations to help enhance data narratives
• Contextualize all findings and insights with marketing knowledge and media landscape considerations

Qualifications

You Have:

• 8+ years experience in an analytics role; Full-funnel Paid Marketing analytics specific role highly preferred, with specific experience in performance marketing analytics
• Experience with digital media strategy and the ever-evolving attribution landscape
• Experience and knowledge of data warehousing and business intelligence, with emphasis on data architecture, sourcing, reporting and analytics through the entire project lifecycle
• Experience with business intelligence reporting and building data visualizations and dashboards (e.g. Looker, ThoughtSpot, Tableau)
• Experience with marketing acquisition tactics through various paid media channels such as SEM, display, social.
• Experience focusing just as much on the delivery, insights and the "so what" of the data as much as the technical craft of extracting them
• Experience using data for storytelling to technical and non-technical audiences
• Experienced in taking vague questions and crystallizing them into impactful experiments, analyses, or models
• Experience with data extraction and analysis using SQL/Google (schema and ETL design, and query optimization) and comfortability operating in Google Sheets and Google Slides
• Experience applying data-backed hypotheses to solve practical product problems such as customer churn, engagement modeling, or behavioral clustering