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ING

Digital banking and sustainable lending

Pricing Data Scientist

Data ScienceConfirmed live in the last 24 hours
Full-timeRomaniaNo salary listed

About the Job

Requirements

  • A Master's degree in a quantitative field such as Mathematics, Statistics, Economics, Finance, or Computer Science.
  • 3–6+ years of experience in data science, pricing, lending analytics, or revenue management.
  • Strong experience with Python and PySpark, production-grade machine-learning models, and advanced techniques such as elasticity modelling, discrete choice, uplift, constrained optimization, and experimentation.
  • Solid understanding of funding and liquidity, expected loss, capital usage, and return on equity steering, with the ability to translate these into pricing logic and explain results transparently.
  • Ability to independently frame complex business problems, work in cross-functional Agile squads, and take ownership from problem definition through production and governance.
  • Ability to explain complex analytical trade-offs to technical and non-technical audiences.

Responsibilities

  • Design, build, and govern value-based pricing models for retail banking products, supporting lending, deposits, and daily banking growth.
  • Develop loan-level valuation models using net present value, Economic Profit, and return on equity, applying full cash-flow logic across the product lifecycle.
  • Incorporate embedded options such as prepayment behaviour, repricing features, and offer periods into pricing and valuation logic.
  • Integrate funding, risk, capital, and tax components, including funds transfer pricing, Expected Loss, and capital usage, in line with global risk-based pricing principles.
  • Build customer behaviour models, including price elasticity, discrete choice, and 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 return on equity under defined risk-appetite and governance constraints.
  • Run scenario simulations and experiments, including A/B tests and pilots, to assess margin-volume trade-offs and market dynamics.
  • Operationalize models on the analytics platform, such as DAP or Google Cloud Platform, including monitoring, drift detection, and periodic recalibration.
  • Ensure model governance through documentation, validation packs, iModel registration, and remediation of validation findings.
  • Collaborate with Product, Pricing, Risk, Finance, and Operations teams to align strategic directions and embed analytics into pricing decisions and approvals.

About the Company

ING

Digital banking and sustainable lending

ING provides digital banking and financial services to individuals and businesses worldwide. Its products and services include online and mobile banking, lending, payments, and advisory services designed to be frictionless so customers can make confident financial decisions. ING differentiates itself by focusing on sustainable choices, responsible lending, and sharing knowledge to help customers and partners realize their visions for a better future. The bank emphasizes empowerment over judgment and aims to finance change, partner with customers, and continuously innovate in a sustainable way. Its goal is to help people and businesses progress toward their goals while reducing barriers and making banking easier and more responsible.

Company size
10,001+
Company stage
IPO
Headquarters
Amsterdam, Netherlands
Founded
1991

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