Director, Analytics AI & Data Platforms
Company Description
At PayNearMe, we’re on a mission to make paying and getting paid as simple as possible. We build innovative technology that transforms the way businesses and their customers experience payments. Our industry-leading platform, PayXM™, is the first of its kind—designed to manage the entire payment experience from start to finish. Every click, swipe or tap is seamless, fast and secure, helping non-commerce businesses boost customer satisfaction, accelerate payments, and reduce costs.
Our single platform handles it all: cards, ACH, digital wallets such as PayPal, Venmo, Cash App Pay, Apple Pay and Google Pay, and even cash at more than 62,000 retail locations nationwide. Today, thousands of businesses across consumer lending, iGaming and online sports betting, property management, and tolling trust PayNearMe to deliver a payment experience that drives real results.
In September 2025, we raised a $50 million Series E funding round to accelerate our growth.
We’re a team of 300+ employees across 41 states, headquartered in Silicon Valley with satellite offices in Dallas, TX and Holmdel, NJ.
Join us and be part of a team that’s shaping the future of payments—one experience at a time.
- Snowflake
- Dataiku
- dbt
- Fivetran
- Apache Iceberg on Amazon S3
- Looker & LookML
- SQL, Python
- AWS
- MySQL, PostgreSQL
- Gitlab
- Monte Carlo
- Terraform, OpenTofu
- RDS Database Insights and Datadog
Responsibilities:
Strategic Leadership & AI Vision
- 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.
Predictive Analytics & Analytical AI Leadership
- 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.
Data Platform & Architecture Leadership
- 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.
Cross-Functional Business Partnership
- 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.
Team Leadership & Organizational Development
- 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.
Governance, Risk & Compliance
- 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.
Requirements:
- 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.
Preferred:
- 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.
Annual Salary Range
$225,000 - $250,000 USD
Why Join Us?:
- 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
PayNearMe strives to create a workplace where all employees thrive. Our core values represent who we are today and we take pride in the way we work with each other as well as with our stakeholders.
We’re in this together to do the right thing. We deliver real results we are proud of while remaining respectful, transparent, and flexible.
PayNearMe is an equal opportunity employer. We are diligently and thoughtfully working towards cultivating a diverse workforce which in turn, enhances our products and services for the communities we serve. Applicants who represent all backgrounds are strongly encouraged to apply.
CALIFORNIA CONSUMER PRIVACY ACT: APPLICANT NOTICE
Effective Date: January 1, 2020
Last Reviewed on: December 23, 2019
PayNearMe, Inc. (the “Company”) is providing you with this Notice (“Notice”) to inform you about:
- the categories of Personal Information that the Company collects and maintains about applicants; and
- the purposes for which the Company uses that Personal Information.
For purposes of this Notice, “Personal Information” means information that identifies, relates to, describes, is capable of being associated with, or could reasonably be linked, directly or indirectly with, a natural person that the Company may collect in connection with screening applicants for job openings at the Company.
- Identifiers and Professional or Employment-Related Information. The Company collects identifiers and professional or employment-related information, which may include some or all the following: real name, nickname or alias, postal address, telephone number, e-mail address, membership in professional organizations, professional certifications, language skills, and current and past employment history. The Company collects this Personal Information to evaluate previous job performance and consider applicants for positions, to develop a talent pool and plan for succession, to conduct applicant surveys, to maintain an internal applicant directory and for purposes of identification, to promote the Company as a place to work, and for workforce reporting and data analytics/trend analysis.
- Personal Information Categories from Cal. Civ. Code § 1798.80(e). The Company may collect categories of Personal Information listed in Cal. Civ. Code §1798.80(e), other than those already listed above, (a) to the extent necessary to comply with the Company’s legal obligations, such as to accommodate disabilities; (b) to conduct a direct threat analysis in accordance with the Americans with Disabilities Act and state law; (c) for occupational health and safety compliance and record-keeping; and (d) to respond to an applicant’s medical emergency.
- Characteristics of Protected Classifications Under California or Federal Law. The Company may collect information about race, age, national origin, disability, sex, and veteran status as necessary to comply with legal obligations, including the reporting requirements of the federal Equal Employment Opportunity Act, the federal Office of Contracting Compliance Programs (applicable to government contractors), and California’s Fair Employment and Housing Act. The Company collects this Personal Information for purposes including: to comply with Federal and California law related to accommodation. The Company also collects this category of Personal Information on a purely voluntary basis, except where required by law, and uses the information only in compliance with applicable laws and regulations.
- Education Information. The Company collects education information such as resumes and graduation records. The Company collects this Personal Information to determine suitability for roles, to determine eligibility for training courses, and to assist with professional licensing.
- Profile Data. The Company may collect profile data, including the following: psychological assessments, behavior analyses, or other profiling of its applicants. The Company collects this Personal Information to determine aptitude for certain positions and job assignments as well.
- Background Screening Information. In the event that an applicant is given a formal job offer, the Company collects background screening information prior to hiring, including results of the following types of background screening: criminal history; sex offender registration; motor vehicle records; credit history; employment history; drug testing; and educational history. The Company collects this Personal Information to screen for risks to the Company and its clients, and continued suitability for their jobs and to evaluate applicants for promotions.
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