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Director of Data Analytics, Science & AI Enablement

Director of Data Analytics, Science & AI Enablement

ChargebeeChennai, India
30+ days ago
Job description

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
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