Sr Director, Enterprise Analytics & Business Intelligence

The Senior Director, Enterprise Analytics & Business Intelligence will rebuild and lead the enterprise analytics function at Learning Care, driving strategy, spend and business decision-making across marketing, retention, product, operations, and digital through rigorous measurement, forecasting, and modeling of revenue flow-through. This role will also take input from the finance partner to build operational flow through of labor and food spend to make business decisions on operational spend supporting our 1100 school chain in expense management and EBITDA flow through.  This role is accountable for standing up a modern analytics operating model, building and developing a multi-tier team — from the ground up, and presenting regularly to the Executive Leadership Team on business performance, enterprise forecasting, and the measurement operating system that connects marketing activity to registration, enrollment, utilization, and EBITDA across the 11-brand portfolio. This role owns the analytics strategy, platform roadmap input, and the executive narrative that informs capital allocation and strategic direction for the enterprise.

Key Responsibilities:

1. Develop, adapt, and execute enterprise-wide analytics strategy spanning marketing, retention, product, operations, and digital to achieve key business objectives, with accountability for the performance and results of this large, strategically important function across the 11-brand portfolio, making decisions guided by enterprise and functional strategies and objectives.
2. Develop, adapt, and execute enterprise level insights to support the DM coaching and care save teams to validate and develop strategy for our field, customer care and call center organizations.
3. Own the enterprise voice-of-the-family measurement strategy, directing the design, governance, and continuous evolution of the NPS and enrollment survey program and its reporting, and translating feedback from prospective, existing, and exiting families into strategic recommendations and next best actions for senior leadership.
4. Lead revenue flow-through modeling that connects marketing investment to leads, registrations, enrollments, utilization, and EBITDA, and defends the models in enterprise forecasting and investment review cycles.
5. Build and maintain the enterprise measurement operating system including methodology standards, metric definitions, governance frameworks, and the reporting cadence that drives decision-making across functions.
6. Rebuild the enterprise analytics multi-tier function from the ground up, including the operating model, intake process, prioritization framework, delivery cadence, and quality standards that make analytics a trusted and repeatable business capability.
7. Present regularly to the Executive Leadership Team on business performance, enterprise forecasting, measurement findings, and strategic recommendations, owning the quantitative narrative that ties digital investment to enterprise outcomes and the strategic horizon.
8. Provide leadership and direction through team by building, hiring, coaching, and scaling a multi-tier team of analytical talent and establishing a durable analytics function with clear career ladders, performance management, and succession planning.
9. Drive analytics platform strategy and roadmap input including Fabric EDW evolution, Palantir ontology, data product priorities, and vendor engagement with partners across the enterprise analytics stack.
10. Manage senior vendor and consultant relationships at enterprise scale, holding delivery partners accountable for measurable business outcomes and ensuring Learning Care owns the intellectual property, methodology, and data assets generated.
11. Other duties as assigned.

Minimum Qualifications:

1. A bachelor's degree in business, finance, statistics, economics, data science, or a related field is required.
2. 10+ years of progressive experience in analytics, business intelligence, finance, or data science leadership is required, with at least 5 years in a director-level or above role.
3. Experience leading enterprise analytics or BI functions in a multi-brand or multi-business-unit consumer organization is required.
4. Demonstrated experience building revenue flow-through models that connect business inputs through a multi-stage funnel to financial outcomes, and defending them in executive review cycles, is required.
5. Demonstrated experience building or rebuilding an analytics or BI function from the ground up, including operating model design, intake and prioritization frameworks, and quality standards, is required.
6. Experience hiring, coaching, scaling, and retaining analytical teams including performance management and succession planning is required.
7. Experience presenting regularly to executive leadership teams on analytical findings, enterprise forecasting, and strategic recommendations is required.
8. Hands-on fluency with modern data warehouses and BI platforms including Microsoft Fabric, Snowflake, Databricks, Power BI, or Tableau is required.
9. Hands-on fluency with SQL and statistical modeling tools (Python, R, or equivalent) is required at a working level sufficient to validate team outputs.

Preferred Qualifications:

1. A master's degree in business administration, data science, applied statistics, or a related quantitative field is preferred.
2. 15+ years of total experience with 8+ years in analytics leadership is preferred.
3. Experience in private equity-backed consumer services businesses operating on a defined strategic horizon is preferred.
4. Experience in education, childcare, healthcare, or other family services in consumer industries is preferred.
5. Experience with Palantir Foundry, customer data platforms, or ontology-based decision systems is preferred.
6. Experience with marketing mix modeling, incrementality testing, or causal inference at enterprise scale is preferred.
7. Experience partnering with CFO or Finance organizations on enterprise forecasting is preferred.
8. Experience owning analytics strategy during a strategic transaction or liquidity event is preferred.
9. Experience leveraging AI and machine learning capabilities to augment analytical workflows, automate insight generation, or improve forecasting accuracy is preferred.

Knowledge, Skills and Abilities:

1. Ability to translate complex analytical findings into executive narratives that inform capital allocation and strategic direction.
2. Working knowledge of revenue recognition, utilization economics, and the operating levers that drive EBITDA in a multi-brand consumer services business.
3. Ability to defend forecasts, models, and investment business cases to Executive Leadership Team, CEO, Board, and investor audiences.
4. Executive communication skills including the ability to say 'the data does not support this' and propose what evidence would be required to change that view.
5. Ability to influence enterprise strategy without direct authority across marketing, operations, finance, and product leadership.
6. Working knowledge of modern analytics platforms, data engineering fundamentals, and the trade-offs between buy and build in the analytics stack.
7. Ability to build analytical talent at scale including identifying high-potential analysts, developing them into senior individual contributors or managers, and retaining them through career progression.
8. Comfort operating in ambiguous and fast-moving environments where measurement standards are still being established.
9. Excellent customer service skills with both internal and external customers.
10. Capable of working with frequent interruptions and changing priorities.
11. Effective communication skills, written, verbal, and interpersonal.
12. Proficient time management, organizational skills, and ability to meet established deadlines.

Specific Technical Experience

• Marketing Analytics: Significant experience  with marketing attribution, marketing mix modeling, incrementality testing, and customer acquisition economics.
• Digital Analytics: Significant experience working with of Google Analytics 4 (GA4), digital attribution, conversion measurement, funnel analytics, and customer journey tracking.
• SQL: Advanced SQL proficiency for querying, joining, transforming, and validating large enterprise datasets.
• Business Intelligence: Hands-on expertise with Power BI or Tableau, including dashboard development, data visualization, and executive reporting.
• Statistical Modeling: Proficiency in Python or R for forecasting, regression, predictive modeling, and statistical analysis.
• AI & Generative AI: Experience leveraging Claude, ChatGPT, or similar AI tools to accelerate analytical workflows, generate insights, automate reporting, and improve analytical productivity.