Lead Data Product Manager – Fintech Engineering

Job not on LinkedIn

🔥 38 minutes ago

🇵🇱 Poland – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 14%

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InPost Group

WebsiteLinkedInAll Job Openings

10,000+ employees

🛍️ eCommerce

🚗 Transport

📦 Logistics

eCommerce • Transport • Logistics

InPost Group is Europe's leading e-commerce enablement platform, specializing in out-of-home delivery services. Founded in 1999 by CEO Rafal Brzoska, InPost provides cost-effective and environmentally friendly delivery solutions through a robust network of Automated Parcel Machines (APMs) and courier services. The company also offers pick-up drop-off (PUDO) services, enhancing convenience and efficiency for e-commerce merchants across Europe. InPost is committed to sustainability, reducing carbon emissions significantly in its delivery processes. With operations in countries like Poland, France, Benelux, the UK, and Italy, InPost continues to expand its innovative technology solutions to drive long-term growth in the e-commerce sector.

📋 Description

• Own data products supporting credit and payments decisions across BNPL and Acquiring & Payments • Own and prioritise the roadmap for feature stores, decisioning and underwriting datasets, and self-serve analytics products • Sequence investment according to commercial and risk impact • Translate credit, underwriting, fraud, and commercial needs into prioritised data-product specifications and acceptance criteria • Partner with the Head of Data Engineering & Analytics and Head of ML & MLOps Engineering to align roadmap, platform capacity, feature-store architecture, and delivery sequencing • Establish AI-first and agentic delivery as the team default • Shape data products with agents, guardrails, evaluations, and human-in-the-loop controls • Lead Data Consultants in AI-first ways of working • Define and track portfolio success metrics, including adoption, self-serve usage, and decisioning-data SLAs • Report progress and trade-offs to the Data Products & Management Director and cross-functional stakeholders • Lead up to three Data Consultants and manage their capacity planning • Work with Databricks lakehouse, feature-store and underwriting datasets, self-serve analytics products, LLM-assisted and agentic tooling, alternative-data providers, and payment-scheme/acquirer partners

🎯 Requirements

• 5+ years in product management for data products or data platforms • Experience leading or coordinating technical and analytical teams, directly or through a matrix • 3+ years of experience in fintech, credit, lending, or payments • Knowledge of BNPL origination, underwriting, and transaction/acquiring flows • Strong data-product strategy and roadmap ownership for feature stores and decisioning datasets • Fluency in point-in-time correctness, freshness, lineage, and self-serve enablement • Ability to convert business, credit-risk, and ML needs into buildable, prioritised specifications • Stakeholder and roadmap management across multiple product lines and delivery teams • Awareness of regulations governing credit and payments data • 2+ years of experience in AI-first data-product leadership, including agents, guardrails, evaluations, human-in-the-loop, and control of agent-loop cost and latency • Experience setting AI-first ways of working, including LLM-assisted analysis and agentic tooling • Strategic and outcome-focused approach, framing data-product decisions as ROI • Ability to translate between Data Engineering/ML and business and risk stakeholders • Ability to influence without direct authority across Credit & Fraud Risk, Engineering, and Commercial teams • Ability to prioritise and re-prioritise roadmaps across two product lines under capacity constraints • Fluent in English (B2+) • SQL proficiency and hands-on data interrogation • Bonus: feature store or ML-enabled decisioning products • Bonus: acquiring/merchant payments data and payment-scheme data structures • Bonus: ML/MLOps fundamentals • Bonus: IFRS 9/credit provisioning data concepts • Bonus: self-serve analytics products for commercial or risk teams • Bonus: Databricks/lakehouse platform familiarity

🏖️ Benefits

• Architectural authority from day one • Greenfield, high-stakes work with design decisions lasting for years • Modern stack and lean, AI-native team • Space to experiment with new technologies and bring them into production • Collaborative, fast-moving environment • Autonomy and accountability • Hybrid work arrangement • B2B contract