Pricing Data Scientist – Analytics

About the role

ING Bank Romania's Analytics team is looking for a Pricing Data Scientist who designs, develops and governs pricing analytics for retail banking products. The role integrates financial and risk drivers into pricing models, runs them on the analytics platform and ensures compliance with Model Risk Management and Data Governance standards. It sits in the Growth Tribe, which focuses on pricing optimization, customer behaviour modelling and scenario simulations.

Key responsibilities

• Design, build and govern value-based pricing models for retail banking products, covering assets and liabilities growth (lending, deposits, daily banking)
• Build loan-level valuation models (NPV, economic profit, RoE) with full cash-flow logic across the product lifecycle
• Incorporate embedded options such as prepayment behaviour, repricing features and offer periods
• Integrate funding, risk, capital and tax components (FTP, expected loss, capital usage) in line with global risk-based pricing principles
• Build customer behaviour models (price elasticity, discrete choice, uplift) to quantify price sensitivity and win probability
• Develop optimization logic and decision rules that recommend price points or bands balancing volume, margin and RoE
• Run scenario simulations and experiments (A/B tests, pilots) to assess margin-volume trade-offs
• Operationalize models on the analytics platform (e.g. DAP / GCP), including monitoring, drift detection and recalibration
• Ensure model governance: documentation, validation packs, iModel registration and remediation of validation findings
• Collaborate with Product, Pricing, Risk, Finance and Operations teams

Required profile

• Master's degree in a quantitative field (Mathematics, Statistics, Economics, Finance, Computer Science)
• 3-6+ years of experience in data science, pricing, lending analytics or revenue management
• Solid understanding of funding and liquidity, expected loss, capital usage and RoE steering
• Ability to work independently in cross-functional Agile squads and communicate complex trade-offs to technical and non-technical audiences

Required skills

• Python (and PySpark)
• Production-grade machine learning models
• Elasticity modelling, discrete choice, uplift and constrained optimization

What we offer

• Hybrid working model
• Monthly benefit budget and extra vacation days based on experience
• Learning through ING Learning Centre, Udemy, Bookster and certifications
• Internal mobility and international assignments
• Modern open offices and a collaborative analytics community