Senior Product Manager (Growth, FinTech)

Hiring for a Client - CIMET

Key responsibilities 1) Product vision & strategy • Define and articulate the vertical product vision aligned to CIMET's business goals and growth roadmap. • Own the product lifecycle from ideation and research to launch and post-release optimisation. • Translate strategy into a focused quarterly bets plan with clear targets. • Identify opportunities to enhance engagement, conversion, lead quality, and retention — including through AI-driven personalisation, intelligent pre-filling, and LLM-powered recommendation surfaces. 2) Roadmap execution & agile delivery • Manage and refine the product backlog, balancing strategic priorities, technical debt, and customer needs. • Partner with engineering to ensure crisp scope, acceptance criteria, rollout plans, and predictable delivery. • Lead agile ceremonies as needed: planning, stand-ups, reviews, retrospectives. • Ship iteratively; ensure every release has success metrics and guardrails. • Define and own the AI feature backlog for your vertical: where LLM integration adds genuine value to the user journey, what the evaluation criteria are, and what fallback and failure handling looks like. 3) Metrics ownership & experimentation • Own weekly reporting of funnel performance and drivers: what moved, why, and what we do next. • Establish a steady cadence of experimentation — A/B tests, rollouts, UX improvements — with measurable outcomes. • Ensure measurement hygiene: instrumentation requirements are met and readouts happen on time. • Define and track AI-specific product metrics: model-assisted conversion rate, AI feature adoption, recommendation acceptance rate, and LLM output quality signals. 4) Stakeholder management & communication • Act as the primary link between business leaders, tech teams, and external partners. • Communicate roadmap, priorities, trade-offs, and performance insights to senior stakeholders. • Partner across Australia, India, and the Philippines to maintain alignment on goals and delivery milestones. • Serve as the voice of the customer and ensure user-centric solutions are embedded in every release. 5) Partner ecosystem collaboration • Work with Partnerships/Business Owners to shape partner onboarding priorities and improve partner performance. • Own product readiness and launch gating: data capture, routing behaviour, UX flows, monitoring. • Drive partner feedback loops into the roadmap: acceptance/rejection reasons, SLA breakdowns, failure modes. 6) AI-enabled product development • Identify where LLM-powered features can meaningfully improve the consumer comparison journey: pre- filling eligibility data, surfacing contextual recommendations, simplifying complex offer comparisons, or reducing form friction. • Write product requirements for AI features with the same rigour as any other feature: input/output definition, confidence thresholds, fallback behaviour, human-in-loop requirements, and success metrics. • Collaborate with the AI & Automation SPM and engineering to ship AI features that are production- grade: instrumented, monitored, and with defined rollback criteria. • Stay current on how LLM integration is being applied in consumer FinTech, insurance, and comparison product UX - bring relevant patterns into your vertical proactively. CIMET Senior Product Manager — Vertical Products Confidential — For Recruiter Use Only • Use AI tools actively in your own product practice: research synthesis, PRD drafting, experiment hypothesis generation, competitive analysis, and data interpretation. 7) Innovation & growth • Use data, market trends, and customer behaviour to uncover opportunities that increase adoption and monetisation. • Partner with UX/UI and Marketing to launch improvements that boost customer experience and conversion. • Benchmark performance against competitors and continuously evolve CIMET's comparison experience. 8) Quality & continuous improvement • Ensure UAT readiness and validate outcomes before broad release. • Monitor metrics: engagement, NPS where applicable, conversion, and lead quality. • Collaborate with QA and DevOps to ensure stable, scalable releases and fast incident recovery. • Maintain a feedback loop that translates insights into actionable roadmap items.

Ideal Candidate

• Strong Senior Product Manager — Vertical Products (Fintech, Growth & Conversion) Profile
• Mandatory(Experience 1)- Must have 6+ years of product management experience in an Agile/Scrum setup, including at least 1 year of LLM integration experience — having specified and shipped LLM-powered features in consumer-facing product UX — with proven end-to-end lifecycle ownership (ideation, research, launch, post-release optimisation) across web and/or mobile platforms.
• Mandatory(Experience 2)- Must have a metric-backed track record improving conversion, revenue yield, engagement, or lead quality in a consumer funnel — owned numbers, a steady experimentation cadence (A/B tests, rollouts, readouts), and comfort with analytics: funnels, cohorts, drivers, causal reasoning, measurement hygiene.
• Mandatory(AI Fluency)- Must be fluent with AI — active, habitual use of AI tools (ChatGPT, Claude, Gemini, Perplexity, or equivalent) in daily product practice (research, drafting, analysis, ideation)
• Mandatory(Stakeholder Mgmt)- Must be able to act as the primary link between business leaders, tech teams, and external partners — communicating roadmap, priorities, trade-offs, and performance readouts to senior stakeholders, and working with distributed teams across time zones (Australia, India, Philippines).
• Mandatory(Product Writing & Agile Delivery) - Must have strong product writing — problem briefs, PRD-lite/user stories, experiment plans, decision logs — and deep working command of Agile frameworks and tools (Jira, Confluence; Trello acceptable): backlog management, crisp scope and acceptance criteria, iterative shipping with success metrics and guardrails.
• Mandatory(Company)- Must be from a B2C fintech product company — consumer-facing fintech as core recent tenure (payments, lending, insurance, wealth, comparison/aggregation in financial services).
• Preferred(Skill)- Exposure to LangChain, RAG, or prompt engineering in a product context; experience working directly with data science/ML teams on model-backed features; prior AI features in transactional or financial-services consumer UX.