[Remote] Director, Analytical AI & Data Platforms

Note: The job is a remote job and is open to candidates in USA. PayNearMe is on a mission to make paying and getting paid as simple as possible. The Director, Analytical AI & Data Platforms will lead the transformation of predictive intelligence and AI-enabled decisioning across the payment processing ecosystem, building scalable predictive analytics and machine learning capabilities.

Responsibilities

• Execute a multi-year strategy for enterprise Analytical AI and the modern data platform
• Establish the enterprise framework for predictive analytics, machine learning enablement, AI-driven decision intelligence, and scalable analytical product delivery
• Develop a future-oriented roadmap for Analytical AI capabilities, including: Predictive modeling, Recommendation and next-best-action engines, Intelligent segmentation, AI-assisted analytics, Forecasting and anomaly detection, Decision optimization, Generative AI-enabled analytics workflows
• Define how Analytical AI capabilities integrate with broader enterprise AI initiatives, ensuring alignment across data science, automation, GenAI, and operational AI investments
• Collaborate with Data leadership to evangelize strategic viewpoints to executive leadership on predictive analytics, data platform modernization, and emerging technology opportunities
• Lead the design, deployment, and operationalization of predictive and machine learning models that drive measurable business impact across the payments ecosystem
• Advance enterprise predictive analytics capabilities in areas including: Fraud detection and transaction risk scoring, Merchant segmentation and prioritization, Customer lifetime value modeling, Churn prediction and retention, Revenue forecasting, Payment behavior analytics, Operational performance optimization, Intelligent routing and authorization optimization, Customer and merchant next-best-action engines
• Build scalable and reusable AI/ML experimentation and deployment frameworks across business domains
• Lead development of AI/ML algorithms and analytical models using supervised, unsupervised, ensemble, and probabilistic modeling approaches
• Drive adoption of AI-enabled decisioning and predictive insights within Product, Commercial, Operations, Risk, and Customer Experience organizations
• Establish standards for: MLOps, Model governance, Experimentation, Monitoring and drift detection, Explainability, Responsible AI, AI risk management
• Evaluate emerging Analytical AI, GenAI, agentic AI, and decision intelligence technologies to enhance enterprise analytics capabilities
• Lead the strategic evolution of the enterprise cloud data platform ecosystem
• Establish scalable architectural standards for: Data engineering, Semantic modeling, Data quality and observability, Metadata and lineage, Data governance, AI-ready data products, CI/CD and DataOps, Secure and compliant data access
• Partner with Engineering, Cloud Engineering and Security teams to ensure platform scalability, reliability, interoperability, and cost optimization
• Drive modernization initiatives that improve analytical agility, self-service analytics adoption, and AI readiness
• Serve as a consultative thought partner to senior business stakeholders across: Product, Risk & Fraud, Finance, Operations, Commercial, Marketing, Customer Success, Compliance, Engineering
• Translate business challenges into scalable predictive analytics and AI-driven solutions
• Partner with business and analytics leaders to prioritize use cases and integrate predictive decisioning into operational workflows
• Communicate sophisticated AI and analytical insights to executive and non-technical audiences in clear, actionable business terms
• Drive enterprise adoption of AI-driven decision making and analytical products
• Build, mentor, and scale high-performing teams
• Foster a culture of innovation, experimentation, accountability, and continuous learning
• Promote ongoing AI and analytics skill development through mentorship, hands-on learning, external partnerships, and internal knowledge sharing
• Ensure analytical platforms and AI solutions comply with regulatory, privacy, audit, and security requirements relevant to fintech and payment processing environments
• Partner with Legal, Compliance, Security, and Risk teams to establish governance frameworks for AI data usage
• Define standards for data stewardship, AI transparency, explainability, and ethical AI usage

Skills

• Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Information Systems, or related field required; Master's or PhD preferred
• 10+ years of progressive leadership experience in Data, Analytics, AI/ML, or Data Platform organizations
• 5+ years leading enterprise-scale analytics, data science, or AI engineering teams
• Strong hands-on expertise in predictive analytics, machine learning, recommendation systems, decision intelligence, and AI-enabled analytics
• Deep experience with modern cloud data platforms and analytical ecosystems including: Snowflake, Dataiku, dbt, Fivetran, Apache Iceberg, Looker / LookML
• Strong technical expertise in: Python, SQL, ML frameworks and AI tooling, Cloud platforms such as AWS
• Experience establishing AI/ML operating models and production AI governance frameworks
• Demonstrated success operationalizing predictive analytics and AI capabilities at enterprise scale
• Strong executive communication and stakeholder management skills
• Experience leading within complex, matrixed organizations
• Experience within fintech, payment processing, transaction platforms, fraud analytics, or regulated financial services
• Experience with real-time analytics and streaming architectures
• Familiarity with: MLOps platforms, Feature stores, Vector databases, Semantic retrieval architectures, Agentic AI frameworks
• Knowledge of PCI, SOC2, GDPR, and financial data governance requirements
• Experience integrating predictive AI and analytical AI capabilities with broader GenAI enterprise initiatives

Benefits

• Competitive salary and benefits with growth-company options grant
• Fast- paced and professional work culture
• Stock options with standard startup vesting - 1 year cliff; 4 years total
• $50 monthly communication expense stipend to go towards your phone/internet bill
• $250 stipend to enhance your WFH setup
• Reimbursement for peripheral equipment: monitor (up to $400), keyboard and mouse (up to $200)
• Premium medical benefits including vision and dental (100% coverage for employees)
• Company-sponsored life and disability insurance
• Paid parental bonding leave
• Paid sick leave, jury duty, bereavement
• 401k plan
• Flexible Time Off (our team members typically take off ~3-4 weeks per year)
• Volunteer Time Off
• 13 scheduled holidays

Company Overview