xplor
Xplor Technologies powers the experiences at the heart of everyday life. Through modern vertical software, embedded payments (Xplor Pay), and AI-powered capabilities, we help businesses in fitness, recreation, golf and club, field services, laundry, education, and other membership-based and service-based industries simplify operations, uncover insights, and elevate customer and member experiences. With Xplor Pay, we help businesses get paid quickly and securely – without hidden fees. We built the tech ourselves, and our platform delivers secure, transparent, fast, and accurate payments. And when you become part of our Xplor Pay Direct Sales team, you also become part of the personal connection that strengthens the relationship people have with Xplor products. As Product Manager for Data and Analytics, you will own the discovery, definition, and delivery of Xplor's Data and Analytics product capabilities within the Embedded Payments team. This includes merchant-facing reporting and insights, internal analytics infrastructure, payment data quality and the data layer that powers AI features across the Embedded Payments platform. You will sit at the intersection of fintech data engineering, product analytics, and commercial intelligence — turning raw payment, merchant, and transaction data into products that drive measurable value for Xplor, our partners, and their merchants.
Data Product Roadmap Define and own the Data & Analytics product roadmap for Embedded Payments, prioritising ruthlessly across merchant insights, risk intelligence, and internal data tooling. Work with the Lead Product Manager and Director for Engineering for Data to define and execute the product vision for the Global Embedded Payments platform. Merchant Analytics Own the merchant-facing reporting and insights product — including transaction dashboards, settlement reports, reconciliation tools, and cohort-level performance analytics. Define self-service analytics capabilities for our SaaS BMS’s: embedding data and insights directly into partner software products via APIs or embeddable components or bringing to life in our our Payments Merchant Portal. Work with Design and Engineering to build intuitive, accurate, and performant data experiences — ensuring merchants can act on their data without requiring analyst support. Establish feedback loops with the internal teams to continuously improve analytics utility and drive product stickiness. Payment Data Quality & Governance Define and enforce data quality standards across the Embedded payments data pipeline — from transaction ingestion through to reporting and downstream AI models. Own the data product's semantic layer: ensuring consistent definitions for metrics like TPV, net revenue, activation rate, chargeback ratio, and settlement accuracy across all surfaces. Work with Engineering and Data Engineering to build observable, trustworthy data pipelines with SLA-backed freshness and accuracy guarantees. Develop a data governance framework appropriate for a PCI-DSS environment — covering data classification, access control, retention, and merchant data privacy obligations across APAC, UK, and NA jurisdictions. Risk, Fraud & Compliance Intelligence Collaborate with Risk, Compliance, and Engineering to define data products that power fraud detection models, dispute management workflows, and AML screening. AI-Augmented Product Practice Embed AI tools across the analytics product lifecycle: use LLMs to accelerate synthesis of data quality issues, competitive teardowns, stakeholder interview notes, and PRD drafts — operating at materially higher output than a traditional PM. Define the product requirements for AI-powered analytics features within the Global Embedded Payments Platform: natural language querying of payment data, anomaly explanation, and predictive merchant health scoring. Work closely with Data Engineering to scope, validate, and ship ML-powered features — including evaluation criteria, feedback loops, and guardrails for model behaviour. Champion AI tool adoption within the Embedded Payments product team and document effective workflows that peers can replicate. Stakeholder & Cross-Functional Collaboration Partner with Finance, Risk, Compliance, Commercial, and Engineering to align on data definitions, KPI frameworks, and reporting standards. Serve as the primary product manager for data squad deliverables — running sprint ceremonies, writing acceptance criteria, and managing backlog prioritisation. Present data product roadmap and outcomes to senior leadership on a regular cadence. Required 3+ years of product management experience, with at least 2 years owning data, analytics, or intelligence products in a fintech, payments, or financial services context. Strong understanding of payment data: transaction flows, settlement, reconciliation, chargeback lifecycle, and how each generates structured data with specific quality and latency requirements. Hands-on SQL proficiency — comfortable writing and interpreting queries to validate data, investigate anomalies, and size opportunities without needing analyst support. Experience working with modern data stacks: data warehouses (Snowflake), BI tools (PowerBI, Tableau, Metabase), and event tracking platforms. Proven ability to translate ambiguous business problems into well-scoped data products with clear success metrics. Demonstrated understanding of data governance, privacy regulation (GDPR, PDPA, or equivalent), and data quality frameworks in a regulated fintech environment. Proficiency with AI productivity tools (Claude, ChatGPT, Cursor, or equivalent) — with concrete examples of using AI to increase PM output quality and speed. Comfortable working across time zones in a globally distributed team (India + APAC + UK + NA). Preferred Experience with embedded analytics or data-as-a-product — delivering analytics capabilities via API, SDK or Embeddable Components to partners (ISV / SaaS). Familiarity with ML/AI product development: defining model requirements, evaluation frameworks, feature stores, and human-in-the-loop workflows. Understanding of fraud detection and AML data products: rule engines, model scoring pipelines, and real-time transaction monitoring. Experience with PCI-DSS data environments and the specific constraints on cardholder data storage, access, and processing. What does it mean to work for Xplor? Our five core values guide us from how we hire and recognise our team members to how we interact with our customers day to day: Find a better way Do the right thing Say it straight Win together Own the outcome If these values sound like you, and describe people you want to work with, you will thrive at Xplor. As an Xplorer, you will be part of a global network of talented colleagues who will support your success. We look for commonalities and shared passions and give people the tools they need to deliver great work and grow at speed. Ready to apply? To start your application, please submit your resume, and we will be in touch as soon as we can. Please include the word "moonshot" at the top of your message to the Hiring Manager so that we know you took the time to read our job ad. We kindly ask you to apply through our careers portal or external job boards (LinkedIn, Naukri, Indeed, etc) only . Please don't send your application via email. They will not be forwarded. More about us More than 130,000 businesses in 72+ countries rely on Xplor to run their day and get paid, processing over $47 billion in payments annually. Our connected ecosystem helps operators spend less time managing complexity and more time delivering the experiences that matter most. Xplor is backed by world-class investors Advent International, Battery Ventures, and Silver Lake. Good to know To be considered for employment, you must be legally authorised to work in the location (country) you're applying for. Xplor does not sponsor visas, either at the time of hire or at any later time. To learn more about us and our products, please visit xplor.com/careers/ . We also invite you to check out our Candidate FAQs for more information about our recruitment process xplor.com/recruitment-faqs/ . EEO and Artificial Intelligence We believe in transparent hiring. We use an applicant tracking system that includes artificial intelligence enabled features to assist with the screening and assessment of job applications, such as candidate scoring or ranking. These tools support our recruitment process, but all hiring decisions are made by our recruitment team following human review. We do not rely on artificial intelligence to make final hiring decisions. Find our Candidate AI Usage guidelines here . Xplor is committed to providing equal opportunities in employment and creating an inclusive work environment. We provide equal opportunities to all our employees and to all eligible applicants for employment in our company. We do not unfairly discriminate on any ground, including race, religion, color, ancestry, marital status, gender, sexual orientation, age, nationality, ethnic origin, disability or any other category protected by applicable law. We make it a priority to respond to every applicant.