Senior Manager -Data Analytics, Science & AI EnablementChargebee • India

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Senior Manager -Data Analytics, Science & AI Enablement

Chargebee • India

5 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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