[Hiring] Head, CRM @Moniepoint

Role Description

The Head of CRM will be the strategic and technical owner of Moniepoint's entire customer relationship management function. You will architect the lifecycle marketing engine from first principles — from raw data events to revenue-generating automation — across multiple markets, languages, and time zones. This is not a purely strategic role; we expect you to be deeply hands-on in Braze, comfortable reasoning about data schemas, and ruthless about measurable ROI.

You will lead a team of CRM managers, lifecycle specialists, and data/MarTech analysts, working in close partnership with Product, Data Engineering, and Growth.

Key Responsibilities

• Braze Platform Ownership & Architecture
  • Own the full Braze platform architecture — from SDK integration strategy to campaign delivery infrastructure.
  • Design and govern the event taxonomy and custom attribute schema: define naming conventions, data types, cardinality constraints, and deprecation policies for all custom events and user attributes ingested into Braze.
  • Oversee Braze SDK instrumentation (iOS, Android, Web) in collaboration with engineering — including session tracking, custom event firing logic, purchase events, and SDK configuration (flush intervals, geofencing, push primer logic).
  • Architect Braze Currents pipelines to route raw engagement data (sends, opens, clicks, conversions, churn signals) into the data warehouse for closed-loop attribution and reporting.
  • Master the use of Liquid templating for deep personalisation at scale — including conditional logic, content blocks, connected content calls, and aborting messages based on real-time attribute state.
  • Design Connected Content integrations to pull live data (exchange rates, transaction history, offer eligibility) into message payloads at send time.
  • Build and maintain Braze Canvas flows for complex, multi-step lifecycle journeys — including branching on event triggers, audience splits, action paths, experiment steps, and post-path analytics.
  • Manage Segment membership logic rigorously: understand the difference between extension segments (SQL-based, evaluated at send), standard segments (evaluated on ingestion), and the performance implications of each at scale.
  • Govern data point consumption as a core operational metric — audit event instrumentation to eliminate unnecessary data point inflation, enforce attribute update batching practices, and maintain a data point budget aligned with contractual limits.
  • Manage user identity resolution in Braze: alias lifecycle (anonymous → identified), changeUser() call strategy, merge behaviour, and the downstream effects on campaign eligibility and suppression lists.
• Lifecycle Marketing Strategy & Execution
  • Define and own the full customer lifecycle framework: Acquisition → Onboarding → Activation → Engagement → Retention → Win-back — with distinct KPIs, triggers, and success metrics for each stage.
  • Build multi-channel orchestration across Push Notifications, In-App Messages, Email, SMS, and WhatsApp — with channel selection logic driven by user preference data, permission state, and engagement history.
  • Develop behavioural trigger logic based on custom events (e.g., transaction_initiated, kyc_step_completed, send_money_abandoned, first_remittance_sent) to fire contextually relevant messages at the right moment in the user journey.
  • Implement frequency capping, suppression logic, and re-eligibility windows as first-class citizens of every campaign — not afterthoughts.
  • Own localisation infrastructure: template versioning by language, locale-aware send-time optimisation, and compliance with per-market communication regulations (NDPR, GDPR, etc.).
• A/B Testing & Experimentation
  • Build a structured experimentation programme grounded in statistical rigour: define hypothesis frameworks, determine appropriate sample sizes using power analysis, select primary and guardrail metrics, and enforce minimum detectable effect thresholds before tests launch.
  • Use Braze's native A/B and multivariate testing (Winning Variant, Personalized Variant) correctly — understand the difference between a frequentist winning variant selection and a Bayesian personalised variant model, and know when each is appropriate.
  • Extend experimentation beyond copy/creative into journey-level experiments: test trigger timing, channel sequencing, Canvas path logic, and re-engagement cadences using Braze Canvas Experiment Paths.
  • Maintain a test log and learnings repository — every test must have a documented hypothesis, result, confidence interval, and a decision record that informs the next iteration.
  • Establish a culture where no significant CRM change ships without a test plan, and where inconclusive results are treated as valuable data, not failures.
• ROI & Commercial Impact
  • Own CRM's contribution to top-line revenue metrics: transaction volume uplift, remittance send frequency, product cross-sell (e.g., savings, loans, cards), and churn reduction.
  • Build incrementality measurement frameworks — use holdout groups at the Canvas level to isolate the true causal lift of CRM campaigns, separate from organic behaviour.
  • Define and track a CRM P&L: measure cost per send by channel, revenue per message, and LTV impact of lifecycle interventions.
  • Deliver regular CRM performance reviews to the executive team with clear attribution, cohort analysis, and forward-looking forecasts.
• Team Leadership & Cross-functional Partnership
  • Build, manage, and mentor a high-performing CRM team (lifecycle marketers, CRM analysts, MarTech specialists).
  • Partner with Data Engineering to ensure event instrumentation meets CRM requirements — act as the business owner of the CRM data contract.
  • Partner with Product to align in-app behaviour triggers with CRM follow-up flows.
  • Partner with Compliance and Legal to ensure all campaigns meet opt-in, opt-out, and data residency requirements across all active markets.

Qualifications

• 8–10+ years in direct-to-consumer marketing, with a strong bias toward growth, lifecycle, or CRM functions.
• 4+ years in a managerial or leadership role, with direct reports and cross-functional accountability.
• Proven track record in fintech, remittance, payments, or consumer banking — candidates who understand the nuance of financial product activation and compliance-aware marketing are strongly preferred.
• Demonstrated experience operating across multiple markets, languages, and time zones — including managing localisation workflows, market-specific regulatory constraints, and culturally adapted messaging strategies.

Requirements

• Expert-level command of Braze Canvases: multi-step flows, action-based triggers, audience paths, experiment steps, post-path analytics.
• Deep understanding of Braze's data model: the distinction between custom events, custom attributes, purchase events, and nested/array attributes — and the data point cost implications of each.
• Hands-on experience designing event schemas: naming conventions, property typing, event deduplication strategies, and coordinating instrumentation with mobile and web engineers.
• Proficiency in Liquid templating within Braze: conditional personalisation, content blocks, aborting sends via {% abort_message %}, and connected content integration patterns.
• Experience with Braze Currents and understanding of the raw event schema exported to S3/GCS/Snowflake.
• Solid understanding of Braze Segments vs. Segment Extensions, their evaluation timing, and performance trade-offs at scale.
• Experience managing Braze's identity layer: anonymous user handling, alias assignment, changeUser() strategy, and merge/orphan prevention.
• Familiarity with Braze SDK configuration best practices across iOS, Android, and Web.
• Understanding of Braze's send-time optimisation, rate limiting, and delivery controls (e.g., quiet hours, frequency capping, IP warming for email).
• Ability to write and interpret SQL for audience segmentation, campaign analysis, and funnel debugging.
• Strong working knowledge of cohort analysis, retention curves, and LTV modelling.
• Experience with A/B test design: statistical significance, p-values, confidence intervals, sample size calculation, and avoiding common pitfalls (peeking, multiple comparisons).
• Comfortable working with data warehouses (Snowflake, BigQuery, or equivalent) and BI tools (Looker, Metabase, or equivalent).
• Strong communicator who can translate technical CRM logic into business outcomes for exec audiences.
• Experience building CRM functions from an early or growth stage — not just maintaining mature programmes.
• High ownership mentality: you will be judged on revenue outcomes, not activity.

Nice to Have

• Experience with Braze Catalogs for product feed-driven personalisation.
• Familiarity with mobile push best practices: payload size limits, rich push, push TTL, and delivery vs. open-rate optimisation.
• Exposure to WhatsApp Business API campaign management at scale.
• Experience with RFM segmentation or propensity modelling fed into CRM triggers.
• Prior work in regulated financial services with an understanding of marketing compliance (opt-in documentation, suppression list management, PII handling).

What Success Looks Like in Year 1

• A fully documented event taxonomy and attribute schema owned by CRM and enforced via engineering contracts.
• A lifecycle Canvas architecture covering all major user journey stages across all active markets.
• A running experimentation programme with at least one statistically significant test shipped per sprint.
• Measurable, incrementality-verified revenue lift attributable to CRM — presented to leadership with clear holdout methodology.
• A high-performing, coached CRM team with clear OKRs and a roadmap they believe in.

Interview Process

• Interview with our Talent Acquisition team
• Screening test
• Interview with our CGO- Camelia Ganga
• Interview with our Head of Product Instrumentation- Oluwakemi Nwogu
• Interview with Head of Data- Albert Marzo
• Interview with our Braze Consultant