Pricing Data Scientist - Analytics @ ING Bank Romania

About the role

You'll join a deeply analytical team within Retail Banking, focused on turning complex data into clear, actionable insights. The team combines deep analytical expertise with strong business understanding, focusing on high‑impact use cases such as pricing optimization, customer behaviour modelling, and scenario simulations. The environment is collaborative, insight‑driven, and strongly oriented toward real‑world deployment and governance‑ready analytics, not just experimentation. Your day‑to‑day As a Pricing Data Scientist in an Agile Way of Working, you will contribute to the squad's purpose by owning end‑to‑end pricing analytics topics. In this role, you will: Design, build, and govern value‑based pricing models for retail banking products, supporting both Assets and Liabilities growth (lending, deposits, daily banking). Develop loan‑level valuation models (NPV, Economic Profit, RoE) using full cash‑flow logic across the product lifecycle. Incorporate embedded options (e.g. prepayment behaviour, repricing features, offer periods) into pricing and valuation logic. Integrate funding, risk, capital, and tax components (FTP, Expected Loss, capital usage) in line with ING's global risk‑based pricing principles. Build customer behaviour models (price elasticity, discrete choice, uplift) to quantify price sensitivity and competitive win probability. Develop optimization logic and decision rules that recommend price points or price bands balancing expected balance volume, margin, and RoE under defined constraints (risk appetite, governance). Run scenario simulations and experiments (A/B tests, pilots) to assess margin-volume trade‑offs and market dynamics. Operationalize models on the analytics platform (e.g. DAP / GCP), including monitoring, drift detection, and periodic recalibration. Ensure full model governance: documentation, validation packs, iModel registration, and remediation of validation findings. Collaborate with cross-functional teams (Product, Pricing, Risk, Finance, Operations) to align on strategic directions and embed analytics into pricing decisions and approvals. What you bring to the team Education & Experience: Master's degree in a quantitative field (Mathematics, Statistics, Economics, Finance, Computer Science) and 3-6+ years of experience in data science, pricing, lending analytics, or revenue management. Advanced Analytics & Modelling: Strong experience with Python (and PySpark), production‑grade ML models, and advanced techniques such as elasticity modelling, discrete choice, uplift, constrained optimization, and experimentation. Financial & Risk Acumen: Solid understanding of funding & liquidity, expected loss, capital usage, and RoE steering - with the ability to translate these into pricing logic and explain results transparently. Ownership & Collaboration: Ability to independently frame complex business problems, work in cross‑functional Agile squads, and take ownership from problem definition to production and governance. Communication & Storytelling: Strong communication skills, capable of explaining complex analytical trade‑offs to both technical and non‑technical audiences.

Benefits

Additional Information

Mission At ING, we believe in giving people the freedom to grow, explore, and build what matters to them. Analytics plays a key role in making that possible - by turning data into insights that help our customers, our colleagues, and our business make better decisions every day. As part of ING's Analytics community, you will work in an open, supportive setting that values curiosity, ownership, and autonomy, where people are trusted to take responsibility, challenge ideas, and grow - while building analytics solutions that truly matter.

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