# Principal Data Scientist at ING

ING is hiring a Principal Data Scientist. Level rates it Builds AI ●●●●; you can [apply on ING](https://jobsbylevel.com/go/f00bda68-10bc-4e20-913b-c7c0302a4f19?utm_medium=ai-agent).

AI Level 4, AI centrality 85 out of 100. Remote (Istanbul (VADI ISTANBUL PARK)).

## Details

- Company: [ING](https://jobsbylevel.com/companies/ing)
- AI level: AI Level 4 (score 85 out of 100)
- Location: Remote (Istanbul (VADI ISTANBUL PARK))
- Posted: July 13, 2026
- Apply: https://jobsbylevel.com/go/f00bda68-10bc-4e20-913b-c7c0302a4f19?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=principal-data-scientist-at-ing-c42c55

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## Description

Help shape data-driven decision making across ING's global banking network. At ING, we believe data and analytics are fundamental to helping people stay a step ahead in life and business. As part of ING Analytics, you'll join a global Analytics Engineering organization delivering advanced analytical solutions across domains including Pricing, Risk Management, Financial Crime, Customer Intelligence, and People Analytics . Together, these teams support strategic decision-making across ING's international banking operations and help shape the future of data-driven banking. The models and analytical solutions developed within ING Analytics have impact far beyond a single market. A model built in Istanbul can support decision-making processes across multiple European countries and ultimately influence experiences for millions of ING customers. This global reach is one of the unique advantages of being part of ING's international analytics community. Role Summary As a Principal Data Scientist , you will own the end-to-end analytical lifecycle, from problem definition and model development through deployment, validation, and business adoption. Working closely with business stakeholders, Product Owners, Engineers, and Analytics teams, you will transform complex business challenges into scalable data-driven solutions. You will combine advanced statistical modelling, machine learning expertise, experimentation, and business understanding to influence critical decision-making processes across ING. This role offers the opportunity to contribute across multiple analytics domains while helping shape strategic decisions through advanced modelling, experimentation, and analytical insight generation. Whether optimizing customer strategies, improving risk assessments, strengthening financial crime detection capabilities, or supporting pricing decisions, your work will have measurable impact across ING's international banking network. Work Model At ING Hubs Türkiye, flexibility is more than a benefit — it's part of how we work. Our hybrid model is designed to balance collaboration, innovation and personal flexibility. Team members typically work from our Vadistanbul office two days per week during three weeks of the month, while one week each month is fully remote. We also offer additional flexibility throughout August, allowing colleagues to work remotely while staying connected with their global teams. As part of a globally distributed organization, you will collaborate with colleagues across multiple ING locations and contribute to analytical solutions deployed across international banking markets. About You We hire smart people like you for your potential. Our biggest expectation is that you'll stay curious, continue learning, challenge assumptions and contribute to a culture of continuous improvement. You bring strong experience in Data Science, Machine Learning and statistical modelling, together with a proven ability to turn analytical insights into business value. You likely have: 4+ years of experience in Data Science, Machine Learning, Advanced Analytics or related disciplines. A degree in Mathematics, Statistics, Engineering, Economics, Computer Science, MIS or another quantitative field. Hands-on experience delivering end-to-end machine learning projects, from data exploration and feature engineering to deployment and monitoring. Strong Python and SQL skills, together with experience working with large and complex datasets. Experience applying statistical modelling and machine learning techniques to solve real business problems. Excellent communication skills and the ability to collaborate with both technical and non-technical stakeholders. Strong English communication skills in an international environment. Experience with Spark, cloud-based analytical environments, MLOps practices, Git, DevOps, experimentation frameworks, or model deployment processes is considered an advantage. What Will Make You Successful Successful Data

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