Senior Manager - Data Analytics, Science & AI Enablement

Role Overview: You are a visionary and hands-on Director of Data Analytics, Science & AI Enablement at Chargebee. Your primary responsibility is to lead the creation and growth of a data function that powers enterprise-wide AI initiatives. You 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. As a strategic partner to business and technology executives, you will enable insight-driven decision-making and scalable AI applications through modern data architecture and practices. Key Responsibilities: - Lead the development and deployment of machine learning, generative AI, recommendation systems, and predictive models to improve product intelligence and automation. - Build and scale AI capabilities across the platform, including personalization, NLP, anomaly detection, and customer segmentation. - 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. - Build and lead a high-performance team of data scientists, AI/ML engineers, analysts, and data product managers. - Ensure scalable data architecture and high-quality data pipelines in collaboration with Data Engineering. - Oversee data quality, governance, and compliance across all analytical and operational systems. - Drive data availability, quality, and governance across the organization to support AI and advanced analytics initiatives. - Lead the development of dashboards, metrics, and decision-support tools that empower business leaders. Qualification Required: - Bachelors or Masters degree in Computer Science, Statistics, Data Science, Engineering, or related discipline. - Proven experience working in a SaaS or tech environment with subscription-based metrics. - 10+ years of experience in data analytics, data science, or related fields, with at least 3-5 years in a leadership capacity. - 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. - Prior experience with product instrumentation and event tracking platforms. - Experience scaling data teams in a high-growth or startup environment.,