Your mission

Own Application Intelligence at Userlane. You'll shape what we build across App Discovery, HEART Analytics and Portfolio Overview to help enterprise CIOs and IT leaders see where software spending delivers value and where it creates waste. You'll work on opportunities such as:

Defining metrics that hold up: Own the methodology behind our HEART Analytics, deciding what each score measures, how it's calculated, and how it stays credible when data is incomplete.
Delivering outcome-linked metrics: Connect usage data to business outcomes like cost savings, efficiency and compliance risk that enterprise executives can take action on
Building for time-poor executives: Design analytics that bring insights to leaders and answers "what should I do?" not just "what happened?"
Connecting fragmented data sources: Define the integration strategy to combine Userlane behavioural data with cost data from SAM tools, license data from IT asset management and employee data from HR systems,
Transforming insights into action: Define what turns raw usage data into insights that drive action, not just dashboards people look at once
AI adoption governance: Extend analytics to measure how AI assistants and agents affect productivity, cost and ROI.

Your profile

5+ years of product management experience on data/analytics products within a modern product organisation
You've defined a metrics methodology, scoring system or measurement framework that others build on, and you can defend the trade-offs behind it. You're comfortable reasoning about why one calculation approach produces misleading results in a specific scenario and another doesn't.
You start with the business question, not the data. Your first instinct is "what decision are they trying to make?" rather than "what data do we have?"
You hold your ground. You'll work with technically strong colleagues and leaders with well-formed opinions. You can disagree with them credibly, engage with their reasoning, and change your position when the evidence says so, not when the seniority does.
You can hold a credible conversation with data engineers and data scientists about what the data can and cannot prove, and you understand the difference between interesting data and actionable insight
You've worked in enterprise B2B (not B2C product analytics). Healthcare experience is a strong plus
You figure out what works by talking to customers and watching them use the product
You're capable of explaining things to engineers, salespeople, support agents and CEOs alike
You're fluent in English (spoken and written)

Responsibilities

Your mission

Defining metrics that hold up: Own the methodology behind our HEART Analytics, deciding what each score measures, how it's calculated, and how it stays credible when data is incomplete.
Delivering outcome-linked metrics: Connect usage data to business outcomes like cost savings, efficiency and compliance risk that enterprise executives can take action on
Building for time-poor executives: Design analytics that bring insights to leaders and answers "what should I do?" not just "what happened?"
Connecting fragmented data sources: Define the integration strategy to combine Userlane behavioural data with cost data from SAM tools, license data from IT asset management and employee data from HR systems,
Transforming insights into action: Define what turns raw usage data into insights that drive action, not just dashboards people look at once
AI adoption governance: Extend analytics to measure how AI assistants and agents affect productivity, cost and ROI.

Your profile

5+ years of product management experience on data/analytics products within a modern product organisation
You've defined a metrics methodology, scoring system or measurement framework that others build on, and you can defend the trade-offs behind it. You're comfortable reasoning about why one calculation approach produces misleading results in a specific scenario and another doesn't.
You start with the business question, not the data. Your first instinct is "what decision are they trying to make?" rather than "what data do we have?"
You hold your ground. You'll work with technically strong colleagues and leaders with well-formed opinions. You can disagree with them credibly, engage with their reasoning, and change your position when the evidence says so, not when the seniority does.
You can hold a credible conversation with data engineers and data scientists about what the data can and cannot prove, and you understand the difference between interesting data and actionable insight
You've worked in enterprise B2B (not B2C product analytics). Healthcare experience is a strong plus
You figure out what works by talking to customers and watching them use the product
You're capable of explaining things to engineers, salespeople, support agents and CEOs alike
You're fluent in English (spoken and written)