Business Analytics Manager (Remote)

Forbes Advisor•Wilmington, DE

2d•Remote

About The Position

The Business Analytics Manager leads a small team of Analysts aligned to business verticals and partners with General Managers and senior commercial stakeholders to improve understanding of business performance, identify growth opportunities, and support better commercial decisions. This hands-on leadership role combines commercial understanding, analytical expertise, and stakeholder management. The role focuses on the drivers of commercial performance, including traffic acquisition, customer journeys, conversions, partner performance, revenue, costs, and profitability. The manager works with Finance, Revenue Operations, Data Engineering, and other teams to investigate discrepancies and ensure commercial and financial reporting is accurate, explainable, and trusted. The manager translates business questions into analytical requirements and clear recommendations, guides Analysts in communicating insights to technical and non-technical audiences, and identifies opportunities for deeper analysis, forecasting, and experimentation. They also partner with Analytics, BI, Engineering, and Data Science teams to develop scalable reporting and insight products, reusable datasets, and self-service capabilities. The role includes prioritising work, developing the team, reviewing analytical approaches, and remaining technically involved in complex problems.

Requirements

Experience in business analytics, commercial analytics, or performance analytics, including managing or mentoring Analysts.
Strong commercial understanding and experience analysing revenue, profitability, customer acquisition, sales performance, or other key business drivers.
Experience working directly with senior business stakeholders and translating complex questions into analytical requirements and actionable recommendations.
Excellent communication and storytelling skills, including the ability to explain complex findings clearly and influence commercial decisions.
Strong SQL skills and experience working with large, complex datasets.
Experience with BI and visualisation platforms such as Tableau, Power BI, or Looker.
Strong understanding of data quality, reporting accuracy, and reconciling commercial information with financial outcomes.
Experience prioritising analytical work across multiple stakeholders while balancing commercial urgency with analytical quality.
Experience coaching and developing Analysts in technical capability and commercial confidence.
Proactive and curious approach to problem solving, with the ability to identify opportunities rather than simply respond to requests.

Nice To Haves

Experience in performance marketing, affiliate marketing, lead generation, or digital publishing.
Familiarity with marketing and acquisition data from GA4, Google Ads, Meta, or other advertising platforms.
Experience working with Finance, Revenue Operations, or commercial reporting teams.
Experience analysing sales performance, partner economics, conversion funnels, or customer profitability.
Python experience for statistical analysis, forecasting, or advanced analytical work.
Experience collaborating with Data Scientists on predictive modelling, experimentation, or customer analytics.
Experience with Google Cloud Platform, particularly BigQuery.
Experience developing reusable analytical products or self-service reporting capabilities.
Experience working with distributed teams and agile delivery processes.

Responsibilities

Partner with General Managers and senior commercial stakeholders to explain revenue, profitability, and business performance drivers.
Identify performance trends, investigate changes, and recommend opportunities for growth.
Work with Finance, Revenue Operations, and Data Engineering to understand revenue, costs, partner performance, and profitability; investigate discrepancies and support accurate, explainable reporting.
Promote analytical rigour while delivering timely and practical information to stakeholders.
Guide Analysts in turning complex data into clear, actionable insights, explaining performance drivers, challenging assumptions, and recommending next steps.
Identify opportunities for deeper analysis, forecasting, and experimentation.
Translate commercial questions into analytical requirements and collaborate with Analytics, BI, Engineering, and Data Science teams on scalable reporting and insight products.
Identify reusable datasets, dashboards, and analytical approaches that reduce repetitive work and improve consistency and self-service access to trusted information.
Lead and develop a small team of Analysts, supporting their technical development, commercial understanding, and stakeholder relationships.
Prioritise work across business areas, balance immediate commercial needs with longer-term improvements, and focus team capacity on high-value work.
Review analytical approaches and help the team solve complex problems.