Company Description

PayNearMe develops technology to facilitate the end-to-end customer payment experience, making it easy for businesses to accept, disburse and manage payments. Our modern and reliable platform lowers the total cost of payments by increasing acceptance rates, driving self-service and simplifying exceptions. We future-proof our clients’ payments roadmap by including all payment types and channels through a single contract and integration. With PayNearMe, businesses can focus on acquiring new customers while we make accepting payments a modern and seamless experience.

PayNearMe has over 240 employees and is processing over $40B in payments annually. We are a fully-funded private company headquartered in Silicon Valley with our employees distributed across the U.S.

This is an opportunity to join a high-growth, private, venture-backed company during its critical growth phase. Come help us solve our clients’ biggest payment problems.

Job Description

We’re at a pivotal moment: PayNearMe has matured its data foundation and is now ready to shift from data plumbing to data intelligence. While governance, architecture, and self-service analytics remain core responsibilities, machine learning enablement is now a top strategic priority.

What you’ll do & own

We’re looking for a VP of Data who can both elevate our existing platform and spearhead the development of ML capabilities, including building a team, selecting tooling, and partnering across Product, Engineering, and Compliance to bring predictive capabilities to market.

Data Strategy & Platform Leadership:

• Lead overall data architecture evolution (e.g., warehouse optimization, data mesh readiness, real-time data infra).
• Improve the scalability, governance, and usability of our data environment.
• Own tooling and vendor decisions across the data stack.

ML Enablement & Roadmap Ownership:

• Define our ML strategy and roadmap in partnership with Product and Engineering.
• Identify key use cases for ML (e.g., payment success prediction, risk scoring) and scope MVPs.
• Hire or bring in an ML-focused lieutenant to own early implementation and cross-functional integration.

Team Building & Leadership:

• Inherit and grow a high-performing data team across engineering, analytics, and operations.
• Design org structure to support both platform maturity and ML experimentation.
• Mentor Directors and ICs; build a high-trust culture rooted in execution and curiosity.

Cross-Functional Collaboration:

• Work closely with Product, Engineering, Finance, and Compliance to align on data needs and ML use cases.
• Support embedded analysts across teams with centralized tools, standards, and shared context.

Execution & Measurement:

• Balance long-term infrastructure work with near-term business demands.
• Define and track KPIs for data team success (e.g., model deployment cycles, uptime, data SLAs, self-service usage).
• Set ML-specific success criteria: business lift, model accuracy, feedback loops.

Qualifications

You’re a seasoned data leader who’s seen what great looks like, but you’re still willing to be hands-on enough to shape the strategy and lead through ambiguity.

Must-Have Experience:

• 10–15+ years in data leadership, including success in high-growth tech environments.
• Has owned end-to-end data strategy while scaling data platforms and teams.
• Evangelized modern architectures like Snowflake, mesh, and event-based data pipelines
• Proven track record building or enabling ML functions in production environments. Ideally, involving predictive modeling, risk scoring, or personalization.
• Strong understanding of modern stacks: dbt, Snowflake, Fivetran, Airflow, Kafka, etc.
• Fluency in security, compliance, and data access best practices.
• Experienced managing multi-disciplinary data teams (engineering, analytics, science).
• Strong communication skills; can build trust with both technical teams and executive peers.

Nice-to-Haves

• Previous experience in payments, fintech, or regulated industries.
• Familiarity with AI/ML vendor landscape (e.g., Dataiku, SageMaker, Feature Stores).
• Prior experience partnering with Product orgs to shape data-informed feature development.

What Success Looks Like in 12 Months

• Our data mesh implementation is underway and operational
• Business teams are self-sufficient with clean, accessible data
• Clean handoff between core data and ML tracks with clear ownership and velocity.
• One or more ML models successfully deployed and generating measurable impact.
• Improved data accessibility and faster insight cycles across departments.
• A high-functioning, well-aligned data team with strong retention and internal growth.

Current Data Stack:

• Warehousing & Pipelines: Snowflake, FiveTran, Monte Carlo
• Databases: MySQL, PostgreSQL, ElasticSearch, Redis, DynamoDB
• BI Tools: Looker (with openness to others)
• Event Streaming: NATS, structured logs
• AI/ML: Dataiku (early stage), with plans to expand
• Cloud-native and AWS-first, with plans to optimize performance & cost across the stack.

Additional Information

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

Salary Range: $260,000 - $300,000

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.

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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:

1. the categories of Personal Information that the Company collects and maintains about applicants; and
2. 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.

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
6. 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.

Assistance for Disabled Applicants

Alternative formats of this Notice are available to individuals with a disability. Please let us know if you need assistance.

All your information will be kept confidential according to EEO guidelines.