Senior Analyst Engineer - Intelligence Management

The Product Operations team exists to make Product demand absorbable at scale — predictable, sustainable, and governed by a clear operating system, so the business can expand without growing chaos. We run on three principles: intelligence over reporting, flow over heroics, and governance over guesswork.

Intelligence Management is the layer that turns signals into decisions. We instrument the operating system with data, automation, and AI — surfacing risks, opportunities, and pace deviations, and delivering insight that leaders consume directly, without routing a request through an analyst. We move value down the decision lifecycle — Data → Dashboard → Insights → Intelligence → Action — and remove manual toil from the loop, concentrating human judgement where it matters the most. 

You: 

• You are a highly autonomous, technically credible professional who turns messy operational reality into trustworthy intelligence that leaders and teams act on.
• You own and define the approach for ambiguous, high-impact problems — from "what is actually happening across the roadmap?" to automate this loop end-to-end.
• You build the signals, systems, and automated insight that strengthen decision quality and speed, partnering, influencing, and challenging senior leaders with evidence so the department meets its yearly goals with margin instead of heroics.
• You have a good financial acumen and are familiar with ROI metrics.

Your Day to Day: 

In this role, you will autonomously partner with and challenge Product leaders (Directors and above), using data and automation to accelerate decisions and reduce the manual overhead of running the department and create intelligence. You will lead end-to-end or advise according to context, from initial problem framing through to sustained adoption. Your work centers on three pillars:

Intelligence Builder — turning signals into decisions

• Design, build, and operate the signals, dashboards, and automated insights that leaders consume directly — without routing a request through an analyst or ops person.
• Own data quality and trust: every number is accurate and traceable, with documented calculation logic. The intelligence layer is only as credible as the data beneath it.
• Make monitoring self-serviceable — roadmap progress, goal execution, and risk emergence surfaced by default, with human oversight reserved for genuinely complex cases.
• Pair closely with Engineering on upstream instrumentation, defining what data matters and what problems it must solve.

Decision Partner — challenging and enabling leaders

• Translate operational data into decision-ready narratives for senior leadership forums: what is happening, what it means, and what decision it calls for.
• Challenge Product Managers, Engineering Managers, and Senior Leadership with evidence when the data contradicts intuition, acting as a neutral third party in the debate.
• Map and provide the insights that support investment and capacity trade-offs, using historical productivity and capacity data as reference.
• Partner with Delivery Operations and Organizational Effectiveness so intelligence flows into the operating rhythm and the leadership narrative, rather than sitting in a dashboard.

Automation Force Multiplier — removing toil, reclaiming judgment

• Roll out AI and agentic workflows that trigger alerts and action requests to the right individuals, plus push/pull context systems filtered by audience.
• Automate governance and reporting workflows with measurable ROI in hours reclaimed.
• Set standards and best practices for AI-assisted analytical work, modelling AI-first ways of working for the wider team to follow.

You Have & You Know-how: 

• 5–7 years in data/analytics, decision intelligence, analytics engineering, or a similar role with direct engagement with senior stakeholders, ideally in fast-paced B2B Engineering/Product environments.
• Strong hands-on data skills: performant SQL and Python (Pandas), data modelling, pipelines/ETL, and building self-service data products — comfort turning messy inputs into trustworthy signals.
• Demonstrated ability to design automated insight and monitoring systems people actually consume, with data-quality and governance rigour (documented metric logic, no "magic numbers").
• Exceptional communication and collaboration skills, with the ability to influence without authority, simplify complexity, and translate split information into clear narratives for different audiences (from junior ICs to senior leadership); confident challenging senior stakeholders with evidence.
• Solid knowledge of business financials (general concepts — ROI, cost, margin) and the judgment to distinguish a genuine risk signal from noise.
• Ability to operate with autonomy and judgment on ambiguous mandates, owning problems end-to-end from framing through to sustained adoption — a can-do bias that treats ambiguity as an invitation, not a blocker.
• Proficiency in collaborative and BI tooling (e.g., Google Suite, Confluence/Jira, Looker), with AI as your default way of working — you use GenAI and agentic workflows as a force multiplier, not an occasional assistant.
• Learner by nature: high learning agility and a growth mindset — you actively seek what you don't know, especially in emerging AI and automation, and turn it into capability for the team.
• Prior experience in pricing and monetization projects (Plus)

The Product department builds our product to disrupt the financial crime industry from a data-led approach. We partner with our clients using a holistic lens and have result-driven solutions to manage financial risk with a cloud-first platform and a world-class UX interface. Being part of this team, you have a voice in planning, strategizing, and challenging the status quo. Your thoughts and ideas are valued. Our fast-paced and open environment encourages us to lean in, try new things, and discover our potential. We define and act on what could be in tomorrow's world, not on what is today. Join Us! 

 #LI-Remote #LI-MG3