Director of Data Analytics, Science & AI Enablement

Chargebee is seeking a visionary and hands-on Director of Data Analytics, Science & AI Enablement to lead the creation and growth of a data function that powers enterprise-wide AI initiatives. This role will be instrumental in designing, building, and leading a cross-functional team responsible for enterprise data analytics, data science, data governance, and structured data enablement to support advanced AI/ML use cases.

This leader will be a key strategic partner to business and technology executives, enabling insight-driven decision-making and scalable AI applications through modern data architecture and practices.

Roles and Responsibilities:

Data Analytics, Science and AI Enablement Leadership

• Lead the development and deployment of machine learning, generative AI, recommendation systems, and predictive models that improve product intelligence and automation.
• Build and scale AI capabilities across the platform, including personalization, NLP, anomaly detection, and customer segmentation.
• Ensure models are interpretable, ethical, and aligned with business and customer trust standards.

Business Analytics & Insights

• Drive insights into user behavior, product performance, churn prediction, and lifecycle value using customer and usage data.
• Develop dashboards, KPIs, and self-service analytics tools for marketing, product, sales, and support teams.
• Own the customer analytics roadmap to improve onboarding, conversion, retention, and upsell opportunities.

Team Building & Cross-Functional Leadership

• Build and lead a high-performance team of data scientists, AI/ML engineers, analysts, and data product managers.
• Partner with Product, Engineering, Marketing, Sales, Legal, Risk & Compliance, and Customer Success to align data strategy with business objectives and legal requirements.
• Communicate findings to senior leadership and influence roadmap decisions using data-backed recommendations.

Data Infrastructure & Governance

• Collaborate with Data Engineering to ensure scalable data architecture and high-quality data pipelines.
• Oversee data quality, governance, and compliance across all analytical and operational systems (GDPR, SOC 2, etc.).
• Implement scalable data architecture and governance frameworks.
• Oversee data consolidation efforts, master data management, and enterprise data catalog development.
• Ensure compliance with data privacy regulations and internal standards.

Team Leadership & Vision

• Build and lead a high-performing global team of data analysts, data scientists, and data engineers.
• Define and execute a comprehensive data and AI enablement roadmap aligned with company goals.
• Establish the team’s structure, priorities, KPIs, and delivery cadence.

Data & AI Strategy Enablement

• Drive data availability, quality, and governance across the organization to support AI and advanced analytics initiatives.
• Partner with engineering, product, and business stakeholders to identify opportunities for AI/ML solutions and ensure they are supported by reliable, well-structured data.
• Serve as a thought leader for data science, analytics, and AI enablement best practices.

Analytics & Business Intelligence

• Lead the development of dashboards, metrics, and decision-support tools that empower business leaders.
• Foster a culture of data literacy and insight-driven decision making throughout the organization.
• Provide executive-level insights through advanced data analysis and reporting.

Required Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Statistics, Data Science, Engineering, or related discipline.
• Proven experience working in a SaaS or tech environment with subscription-based metrics (e.g., MRR, ARR, CAC, LTV)
• 10+ years of experience in data analytics, data science, or related fields, with at least 3-5 years in a leadership capacity.
• Proven experience in building and scaling data teams in a SaaS or technology environment.
• Strong knowledge of AI/ML concepts, data platforms (e.g., Snowflake, Databricks), and BI tools (e.g., Tableau, Power BI).
• Deep understanding of data governance, data quality, and metadata management.
• Demonstrated ability to lead change in a global, fast-paced, and matrixed environment.
• Excellent communication and stakeholder management skills.
• Deep understanding of SaaS metrics, PLG (product-led growth), and usage-based pricing strategies.
• Prior experience with product instrumentation and event tracking platforms (Mixpanel, Segment, etc.).
• Experience scaling data teams in a high-growth or startup environment