MANAGER, BUSINESS ANALYTICS

FuboNew York, NY
$120,000 - $170,000Onsite

About The Position

The Manager, Business Analytics will be responsible for ensuring the business maintains clear visibility into revenue, trials, conversion metrics, ARPU, lifetime value, acquisition costs, channel performance, and cohort modeling. This role involves identifying relationships and trends in data, presenting findings to marketing teams, and proactively identifying risks and opportunities. The position will also focus on developing customer personas, segmentation analyses, and lifetime value analyses for acquisition campaigns. Additionally, the role will lead company projects focused on revenue generation and cost reduction, analyze company-wide data for inefficiencies, and partner with senior leadership to model revenue expansion opportunities. A key aspect of this role is developing analytical frameworks to identify, monitor, and grow relationships with high-value customer segments, devising new acquisition attribution models, and building predictive models for churn, lifetime value, and upsell potential. The role requires utilizing advanced data tools like SQL, R, and Python, developing mathematical and data visualization models, and serving as a subject matter expert for Google Analytics. Finally, the position involves creating and maintaining dashboards and reports using tools like Tableau, partnering with the data engineering team, and acting as an analytics liaison with cross-functional teams.

Requirements

  • Master’s degree in Data Science or a closely related field
  • 2 years of previous experience as a Data Analyst

Responsibilities

  • Ensure the business maintains clear visibility into revenue, trials, conversion metrics, ARPU, lifetime value, acquisition costs, channel performance, and cohort modeling for a variety of strategic purposes.
  • Identify relationships and trends in data and present findings to relevant marketing teams on a regular basis.
  • Proactively identify risks and opportunities based on planned business actions.
  • Create customer personas and segmentation analyses to identify high-value customers; leverage these to develop look-alike audiences for acquisition and establish benchmarks for retention and engagement.
  • Develop lifetime value analyses for acquisition campaigns at a detailed level.
  • Lead and drive high-visibility company projects focused on additional revenue generation and cost reduction, serving as a key stakeholder in cross-functional initiatives.
  • Analyze company-wide data to identify cost inefficiencies and develop actionable recommendations for cost-cutting across business units.
  • Partner with senior leadership to model revenue expansion opportunities, including new product lines, pricing optimization, and market penetration strategies.
  • Design and execute analyses to quantify the financial impact of proposed strategic initiatives, providing data-driven recommendations to leadership.
  • Develop and maintain comprehensive analytical frameworks to identify, monitor, and grow relationships with the company’s highest-value customer segments.
  • Devise new acquisition attribution models to reduce duplication across channels and maximize CPA efficiency for high-value customer acquisition.
  • Build and maintain predictive models to forecast high-value customer churn, lifetime value, and upsell potential, enabling proactive retention and monetization strategies.
  • Tie Google Analytics data and user demographic and engagement metrics – including viewership, feature usage, household data, and tenure – to high-value customer profiles to generate actionable intelligence.
  • Utilize advanced data tools, including SQL, R, and Python, to identify opportunities and liabilities through rigorous quantitative analysis.
  • Develop mathematical and data visualization models to analyze data trends, generate findings, and produce actionable reports.
  • Serve as the team’s subject matter expert for Google Analytics; analyze campaigns to optimize spend across channels and content groups.
  • Apply advanced information management systems theories, advanced database management, and big data analytics to make data-driven recommendations that optimize acquisition campaigns.
  • Share results of data mining by creating and presenting written reports, tables, charts, and graphs to team members and senior management.
  • Create and maintain new dashboards and reports to track, communicate, and visualize business outcomes using tools such as Tableau, and provide ongoing recommendations to stakeholders.
  • Partner with the data engineering team on data structures, reporting frameworks, and table architecture to ensure analytical accuracy and efficiency.
  • Act as subject matter expert and analytics liaison with cross-functional teams, including Business Development and International, to ensure the success and optimization of their initiatives.
  • Present analytical findings and strategic recommendations to senior leadership in support of major company-wide decisions.
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