AI-First Data Product Lead, Fintech Payments

InPost; Warszawa, Kraków; Hybrid; PLN 240.000 - 480.000; Vollzeit

Benefits dieser Stelle

Hybrid work

B2B contract

Office in Warsaw/Kraków

Zusammenfassung

InPost Pay is building its own fintech platform from the ground up in Poland, offering engineers the chance to shape architecture, core data products, and solutions designed to operate at scale with AI-native engineering.

The Lead Data Product Manager will own the roadmap for feature stores, decisioning and underwriting datasets, translate credit-risk and commercial needs into specs, and lead up to 3 Data Consultants, collaborating with Data Engineering, ML & MLOps, and risk, engineering and

Qualifikationen

• 5+ years in product management for data products or data platforms.
• 3+ years in fintech, credit, lending or payments.
• Experience leading technical and analytical teams.
• Strong data-product strategy and roadmap ownership across data stores.

Aufgaben

• Own the roadmap for feature stores, decisioning and underwriting datasets and self-serve analytics.
• Translate credit, underwriting, fraud and commercial needs into clear specs for Data Eng/ML teams.
• Partner with Data Engineering, ML & MLOps and risk/commercial stakeholders on roadmap alignment.
• Lead data consultants and manage capacity planning across domains.
• Define success metrics and report progress to leadership.

Kenntnisse

Data products

Product leadership

SQL

AI-first

Stakeholder management

Fintech awareness

Databricks

Roadmap ownership

Tools

Databricks

Lakehouse platform

SQL

LLM tooling

Jobbeschreibung

InPost Pay is building its own fintech platform from the ground up in Poland, offering engineers the chance to shape architecture, core data products, and solutions designed to operate at scale with AI-native engineering.

The Lead Data Product Manager will own the roadmap for feature stores, decisioning and underwriting datasets, translate credit-risk and commercial needs into specs, and lead up to 3 Data Consultants, collaborating with Data Engineering, ML & MLOps, and risk, engineering and