Customer Intelligence & AI Lead

We need to output HTML fragment with sections: About the role? The posting includes "Why Choose Bottomline?" and "The Role". We need to use

for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We must only include sections that have real specific content. The posting includes description of role, responsibilities, qualifications, skills, etc. It does not mention Benefits, Pay, Schedule. So we should not include those headings. We need to include About the role (maybe from "Why Choose Bottomline?" and "The Role"?). The instruction: "Do NOT repeat the job title as a heading (the page already shows it)". So we can have About the role heading with description. Then Responsibilities heading with list of responsibilities. Then Qualifications and Skills maybe combined? They have separate sections: Qualifications And Skills Required, Preferred Qualifications And Skills, Core Competencies. We could have Qualifications heading with required qualifications, and Skills heading with core competencies? But they said use headings: Qualifications, Skills. We can put required qualifications under Qualifications, and core competencies under Skills. Preferred qualifications could be included under Qualifications as additional. We must preserve all substantive info. So we need to include bullet lists for responsibilities, qualifications, skills. We must remove boilerplate: EEO, equal opportunity, etc. Also remove "We welcome talent..." and EEO lines. Also remove navigation etc. Not present. We need to preserve all substantive info: The "Why Choose Bottomline?" paragraph is about company; could be part of About the role? Probably yes. We'll include that as prose under About the role. Responsibilities: The posting has many responsibilities broken into sections: Customer Intelligence Strategy & Platform Development, Revenue Opportunity Identification, Partner With The Director, Revenue Strategy & Analytics, Partner With The Director, Revenue Growth Programs, Partner with the Director, Renewal Operations & Commercial Optimization, Artificial Intelligence Strategy & Enablement, Executive Reporting & Business Insights, Success Metrics. We need to list duties as bullet points. Should we include Success Metrics as responsibilities? Probably yes as part of role. We'll capture key bullet points. We need to not invent or summarize away detail. Must preserve all substantive info. That's a lot; we need to include all bullet points from responsibilities. Let's extract them. From text: Customer Intelligence Strategy & Platform Development: - Design, build, and maintain a centralized Customer Intelligence Platform. - Develop a comprehensive Customer 360 environment integrating: * Product usage data * Customer Success data * Customer Support interactions * CRM activity * Contract and renewal data * Financial and billing information * Customer sentiment and engagement metrics - Establish governance, quality standards, and ownership for customer intelligence data. - Create scalable and reusable customer intelligence frameworks supporting the organization's growth objectives. - Develop customer health, customer value, and customer maturity measurement methodologies. Revenue Opportunity Identification: - Develop advanced analytical models that identify revenue growth opportunities across the customer lifecycle. - Create predictive models that surface: * Expansion opportunities * Upsell opportunities * Cross-sell opportunities * Pricing optimization opportunities * Customer retention risks * Revenue leakage - Build recommendation engines that prioritize the highest-value customer actions. - Quantify revenue potential and expected business impact for identified opportunities. - Establish an ongoing pipeline of actionable revenue opportunities for business review and prioritization. Partner With The Director, Revenue Strategy & Analytics: - Build predictive revenue and customer behavior models. - Develop advanced customer segmentation frameworks. - Improve forecasting accuracy through predictive analytics. - Identify leading indicators of churn, retention, growth, and customer health. - Analyze pricing effectiveness and commercial performance. - Deliver executive insights that support revenue planning and strategic decision-making. - Transform descriptive reporting into predictive and prescriptive analytics. Primary Outcome: Enable Revenue Strategy & Analytics to identify, validate, quantify, and prioritize revenue opportunities through data-driven customer intelligence Partner With The Director, Revenue Growth Programs: - Translate identified opportunities into executable growth initiatives. - Prioritize opportunities based on expected revenue impact and likelihood of success. - Develop business cases supporting strategic investments and growth programs. - Measure initiative effectiveness and return on investment. - Monitor execution outcomes and feed learnings back into opportunity identification models. - Create closed-loop reporting between opportunity identification and program execution. Primary Outcome: Deliver a continuously refreshed inventory of high-value growth opportunities ready for implementation across the business. Partner with the Director, Renewal Operations & Commercial Optimization: - Develop predictive customer retention and churn models. - Build renewal risk identification frameworks. - Support pricing optimization and renewal strategy initiatives. - Create AI-assisted renewal prioritization and recommendation engines. - Improve renewal forecasting through predictive analytics. - Enable automation of renewal workflows and decision-support processes. Primary Outcome: Improve customer retention, reduce revenue attrition, and increase renewal performance through advanced customer intelligence. Artificial Intelligence Strategy & Enablement: - Lead evaluation and implementation of AI solutions across Revenue Management and customer-facing functions. - Identify opportunities to leverage AI to improve customer outcomes, productivity, and decision-making. - Develop AI-enabled workflows that automate repetitive analysis and operational activities. - Evaluate emerging AI technologies and their potential business applications. - Establish AI governance, adoption, and performance measurement frameworks. - Serve as the organization's subject matter expert on customer intelligence and AI innovation. Executive Reporting & Business Insights: - Develop executive dashboards, scorecards, and intelligence reporting. - Present strategic findings and recommendations to senior leadership. - Translate complex analytical findings into clear, business-focused recommendations. - Support annual planning, forecasting, operating reviews, and executive decision-making. - Serve as a trusted advisor on customer trends, commercial opportunities, and AI strategy. Success Metrics: list many metrics under categories. We need to include them as responsibilities? Probably as part of role: they are metrics used to measure success. We'll include them as bullet points under Responsibilities maybe as "Success Metrics". But the instruction: Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we have Responsibilities heading; we can include all duties and also success metrics as bullet points under Responsibilities. That's okay. Now Qualifications: Required: Bachelor's degree in Data Science, Analytics, Statistics, Mathematics, Economics, Computer Science, Engineering, Business, or related field. 8+ years of experience in Data Science, Customer Analytics, Business Intelligence, Revenue Analytics, Machine Learning, AI, or related disciplines. Experience building predictive models and advanced analytical solutions. Strong proficiency with SQL, Python, and modern analytics platforms. Experience working with large-scale customer and commercial datasets. Proven ability to translate data into strategic business recommendations. Strong communication and executive presentation skills. Experience influencing cross-functional business leaders. Preferred Qualifications And Skills: Master's degree in Data Science, Analytics, Statistics, Business Analytics, Computer Science, or related field. Experience in SaaS, technology, subscription, fintech, or recurring revenue businesses. Experience building Customer 360, Customer Intelligence, or Customer Health platforms. Experience with Generative AI, Agentic AI, Machine Learning, and predictive analytics solutions. Familiarity with CRM, Customer Success, Support, Product Usage, and Revenue Operations systems. Core Competencies: list: Customer Intelligence, Artificial Intelligence Strategy, Data Science & Machine Learning, Predictive Analytics, Revenue Growth Analytics, Customer Segmentation, Commercial Analytics, Business Intelligence, Executive Storytelling, Strategic Thinking, Innovation & Continuous Improvement, Cross-Functional Leadership. We need to put Qualifications heading with required qualifications (maybe also include preferred as part of Qualifications? Could separate but we only have Qualifications and Skills headings. We could put required under Qualifications, and core competencies under Skills. Preferred qualifications could be added to Qualifications as additional bullet points. Thus:

About the role

Why Choose Bottomline? Are you ready to transform the way businesses pay and get paid? Bottomline is a global leader in business payments and cash management, with over 35 years of experience and moving more than $16 trillion in payments annually. We're looking for passionate individuals to join our team and help drive impactful results for our customers. If you're dedicated to delighting customers and promoting growth and innovation - we want you on our team! The Role The Director, Customer Intelligence & AI is responsible for building and leading the company's customer intelligence and artificial intelligence capabilities, creating a strategic advantage through data-driven insights, predictive analytics, and intelligent automation. This role serves as the intelligence engine of the Revenue Management organization by transforming customer, product, commercial, operational, support, and financial data into actionable insights that drive revenue growth, improve customer retention, and accelerate business performance. The Director will develop a centralized Customer Intelligence Platform that provides a unified view of customer health, value realization, product adoption, retention risk, expansion opportunity, and commercial performance. The role will partner closely with Revenue Strategy & Analytics, Revenue Growth Programs, Renewal Operations & Commercial Optimization, Customer Success, Customer Support, Product, Sales, and Finance to identify opportunities and enable execution. The Mission is to build the organization's customer intelligence and AI capabilities by transforming customer data into predictive insights that uncover revenue opportunities, improve customer retention, enable intelligent automation, and accelerate sustainable business growth. The ideal candidate combines expertise in data science, AI, machine learning, customer analytics, business intelligence, and commercial strategy with the ability to influence decision-making at the executive level.

But we need to avoid repeating job title as heading; we already have About the role heading. The paragraph includes "The Role" and "The Mission". That's fine. Now Responsibilities: We'll create

• for each bullet. Need to include sub-bullets? We can flatten. Let's list all responsibilities bullet points: - Design, build, and maintain a centralized Customer Intelligence Platform. - Develop a comprehensive Customer 360 environment integrating: * Product usage data * Customer Success data * Customer Support interactions * CRM activity * Contract and renewal data * Financial and billing information * Customer sentiment and engagement metrics - Establish governance, quality standards, and ownership for customer intelligence data. - Create scalable and reusable customer intelligence frameworks supporting the organization's growth objectives. - Develop customer health, customer value, and customer maturity measurement methodologies. - Develop advanced analytical models that identify revenue growth opportunities across the customer lifecycle. - Create predictive models that surface: * Expansion opportunities * Upsell opportunities * Cross-sell opportunities * Pricing optimization opportunities * Customer retention risks * Revenue leakage - Build recommendation engines that prioritize the highest-value customer actions. - Quantify revenue potential and expected business impact for identified opportunities. - Establish an ongoing pipeline of actionable revenue opportunities for business review and prioritization. - Build predictive revenue and customer behavior models. - Develop advanced customer segmentation frameworks. - Improve forecasting accuracy through predictive analytics. - Identify leading indicators of churn, retention, growth, and customer health. - Analyze pricing effectiveness and commercial performance. - Deliver executive insights that support revenue planning and strategic decision-making. - Transform descriptive reporting into predictive and prescriptive analytics. - Translate identified opportunities into executable growth initiatives. - Prioritize opportunities based on expected revenue impact and likelihood of success. - Develop business cases supporting strategic investments and growth programs. - Measure initiative effectiveness and return on investment. - Monitor execution outcomes and feed learnings back into opportunity identification models. - Create closed-loop reporting between opportunity identification and program execution. - Develop predictive customer retention and churn models. - Build renewal risk identification frameworks. - Support pricing optimization and renewal strategy initiatives. - Create AI-assisted renewal prioritization and recommendation engines. - Improve renewal forecasting through predictive analytics. - Enable automation of renewal workflows and decision-support processes. - Lead evaluation and implementation of AI solutions across Revenue Management and customer-facing functions. - Identify opportunities to leverage AI to improve customer outcomes, productivity, and decision-making. - Develop AI-enabled workflows that automate repetitive analysis and operational activities. - Evaluate emerging AI technologies and their potential business applications. - Establish AI governance, adoption, and performance measurement frameworks. - Serve as the organization's subject matter expert on customer intelligence and AI innovation. - Develop executive dashboards, scorecards, and intelligence reporting. - Present strategic findings and recommendations to senior leadership. - Translate complex analytical findings into clear, business-focused