Technical Product Manager - Behavioural Analytics

diligentcorporation · Londonmid

In short

▸Diseñar un sistema unificado de métricas de comportamiento para 24+ productos.
▸Construir contratos de datos, estándares de telemetría y modelos para insights de portafolio.
▸El dato es solo el inicio: combinarlo con evidencia cualitativa para entender el 'por qué'.

No se requiere inglés.

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What they ask for

✓Experiencia en gestión de productos con enfoque en datos.
✓Capacidad para definir métricas y contratos de datos claros.
✓Habilidades de comunicación para educar equipos técnicos y no técnicos.
✓Experiencia trabajando con equipos de ingeniería en instrumentación.
✓Capacidad para alinear métricas con objetivos de negocio.
✓Enfoque en la calidad y consistencia de los datos.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

AWSSnowflakeTelemetryData ContractsMetric DefinitionsChange GovernanceBI ToolsPortfolio ReportingInstrumentationVersioned Change Control

Who should you write to at diligentcorporation?

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Here's a summary of the role Data is only powerful when everyone agrees what it means. This is your chance to build a world class product behavioural data system and process from the ground up. We're rebuilding the internal product our teams use to measure product success and end-user value across all our 24+ products in four business units. You'll design the single source of truth: the metric definitions, the telemetry standards, the data contract engineering instruments against, the change governance processes and tooling, and the models that turn behaviour into portfolio insight. You'll educate and support the teams using this internal behavioural data product to set expectations and and plot a rational roadmap for the maturing of this product, helping our user to use the data honestly and wisely. Usage tells you what happened, not why, or whether it mattered. We want someone who sets quantitative behaviour against qualitative evidence and treats the disagreement as the interesting part. AWS/Snowflake is our spine; capture and BI are open decisions you'll help make. Your models feed the business reviews our executive team, CTO and investors use to run the portfolio, and engineering is committed to instrument against your contract. Here's what your first twelve months should look like • First 90 days. Learn the estate, meet the engineers who instrument it, and agree the measurement model for one product end to end — with a defensible adoption number and the qualitative read on what it means. • Three to six months. Data contract published, instrumentation spec landed with engineering, first business unit building against it. Definitions, naming and versioned change control governed. • Six to twelve months. Rolling out across the remaining business units through the BU-aligned analysts, portfolio reporting running on your numbers.

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