Director of Data Analytics, Science

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