<p><strong>The Role</strong></p> <p>We are hiring a Product Manager to work within our Data tribe, specifically owning our data ingestion platform - the engine that identifies, extracts and processes the raw intelligence that powers everything ComplyAdvantage does. You will own the Product requirements for our Ingestion Tooling squad building agentic data ingestion pipelines that extract relevant risk profiles at scale.<br><br>The Data tribe's work is strategically driven rather than customer-driven. The roadmap is shaped by the company's AI roadmap, set at executive level and mapped to a product execution strategy by the VP Product and Product Director. For this squad, that means building a new scalable platform with reusable tools for data identification and extraction, deploying LLMs to improve data processing at scale, and maintaining the pipeline robustness that over 1,000 clients depend on every day. Requirements from the Risk Applications tribe also cascade into Data as derived requirements — particularly around data quality and the ability for clients to explain their decision-making to financial regulators.</p> <p>The PM operates at the intersection of two forces: the strategic execution plan set by the VP Product and Product Director, and the derived requirements flowing from the applications that depend on Data's capabilities.</p> <p>You will work within a dedicated squad alongside an engineering manager and a team that typically includes data engineers, ML engineers and back-end engineers. The Product Manager and Engineering Manager work as peers: you own the commercial and product context, the EM owns the technical context. Neither reports to the other. You operate within a framework set by the Product Director and are expected to use judgement in balancing competing priorities, not to set strategic direction independently.</p> <p>You will operate within a structured product operating model with clear decision rights. Plans are framed as returns on engineering investment, not feature lists. We work in six-week blocks, with quality gates at each stage of the document flow from Plan of Record to PRD to product requirements to implementation. If you have worked in organisations where product management is disciplined and structured, this will feel familiar.</p> <p><strong>What You Will Do</strong></p> <p><strong>Own your product area within the Data tribe. </strong>You are responsible for the roadmap, requirements, research, competitive intelligence and customer insight for the data ingestion platform. You work within strategic direction set by the Product Director but are expected to exercise genuine judgement on priorities, trade-offs and requirements quality. This is substantive work, not order-taking.</p> <p><strong>Build and scale the data ingestion machine.</strong> Define and drive the vision for a scalable platform with reusable tools for data identification and extraction that can serve current and future use cases. Identify value slices that deliver client outcomes while advancing the technical vision — ensuring the platform evolves without accumulating the kind of debt that slows teams down at scale.</p> <p><strong>Balance competing requirements. </strong>Your squad serves the strategic roadmap set by the Product Director and the CPTO, but also receives derived requirements from Risk Apps squads — particularly around data quality, pipeline reliability and regulatory explainability. Balancing these competing inputs, understanding which to prioritise and when, and escalating conflicts that need PD guidance, is a core part of the role.</p> <p><strong>Partner with engineering</strong>. You and your EM are jointly accountable for the quality of product requirements. You sign off on commercial accuracy — does this solve the right problem, does it meet client needs, can it be explained to a regulator; the EM signs off on technical completeness. You need enough technical understanding of data pipelines, ETL/ELT processes, LLM deployment and ML infrastructure to write requirements that engineers can build from and to have productive conversations about feasibility and trade-offs.</p> <p><strong>Work with Data Science.</strong> Data Science works across all tribes and provides research and experimentation that informs product direction. You will work closely with data scientists to understand what is feasible, what research is in progress, and how to translate experimental results — including model training, calibration and deployment decisions — into production capabilities. You help data scientists understand the client impact of their choices. The operating model separates Research (Data Science) from Development (ML Engineers in squads): your squad builds what Data Science has validated.</p> <p><strong>Set and track meaningful metrics. </strong>Define the key metrics that track progress toward the product vision — across pipeline performance, data quality, coverage and client impact. Use these to inform priorities and communicate progress to stakeholders.</p> <p><strong>Provide research and insight.</strong> Synthesise customer feedback, competitive intelligence, usage data and market research into inputs the Product Director can use for planning. Maintain the knowledge base for your product area so that repetitive questions are answered without manual effort.</p> <p><strong>Use AI in your own work. </strong>We expect Product Managers to use AI-assisted workflows for research synthesis, customer feedback analysis, data interpretation and first-draft specifications. This is how we work, not something we aspire to.</p> <p><strong>What We Are Looking For</strong></p> <p>Essential:</p> <ul> <li>3+ years in product management, with at least 2 years working on data products, data pipelines, ML systems or data infrastructure</li> <li>Demonstrated success delivering products where data is the product or a significant component — you understand what it means to be responsible for d