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Salary
≈ $78k – $178k per year (Estimated)
Location
Hybrid (Istanbul, Turkey)
Seniority
Principal · 4+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 29, 2026. First seen by Alion on Jul 13, 2026. ING Group scores B on the Alion truth index.

Overview
Company
Impact
Profile match
ING is a Dutch banking group formed in 1991 by the merger of the postal bank NMB Postbank and the insurer Nationale-Nederlanden, and it was among the first large banks to build a direct, branch-light retail model. It serves retail customers in the Netherlands, Belgium, Germany, Poland, Spain and several other markets through mobile-first banking, and runs a substantial wholesale bank covering lending, transaction services and financial markets for corporate clients. Headquartered in Amsterdam and listed on Euronext, the group divested its insurance operations after the financial crisis to focus on banking.

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 includingPricing, 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 aPrincipal 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 Scientists at ING combine technical excellence with commercial thinking.

You are comfortable working across the full analytical lifecycle and understand that the value of a model is ultimately measured by its business impact.

You:

  • Take ownership of problems and drive them through implementation.
  • Use experimentation and evidence-based decision making to validate new analytical approaches.
  • Design and execute model validation frameworks, including A/B tests and champion-challenger methodologies where appropriate.
  • Balance statistical rigor with practical business needs.
  • Communicate complex analytical concepts in a clear and actionable way.
  • Continuously seek opportunities to improve models, processes and decision-making frameworks.
  • Thrive in collaborative environments where Data Science, Engineering and Business teams work together to deliver value.

Roles & Responsibilities

  • Manage the full analytical lifecycle, from opportunity identification and solution design through implementation, deployment, and business adoption.
  • Analyze large and complex datasets to identify trends, opportunities, and root causes behind business outcomes.
  • Develop machine learning models, statistical frameworks, and analytical solutions that support critical business decisions.
  • Apply advanced analytical techniques to solve challenges across customer, risk, pricing, financial crime, and operational domains.
  • Design and execute experimentation frameworks, including A/B tests and champion-challenger approaches, to assess model effectiveness and business impact.
  • Collaborate with stakeholders across multiple business and technical domains to translate requirements into scalable analytical solutions.
  • Support model deployment, monitoring, and continuous improvement to ensure long-term business value.
  • Communicate analytical findings and recommendations to stakeholders at different levels of the organization.
  • Contribute to ING's Data Science community through knowledge sharing, best-practice development, and continuous innovation.
  • Work closely with Engineering and Platform teams to support production-ready analytical solutions and sustainable model deployment.

Equal Opportunity

Don't meet every single requirement? Don't let that hold you back. Studies show many talented professionals hesitate to apply unless they meet every qualification. If you're excited about this role and believe you can make an impact, we'd love to hear from you.

What We Offer at ING Hubs Türkiye

At ING Hubs Türkiye, we believe that your work should be fulfilling in every way. We pay attention to even the smallest details to ensure that your experience is rewarding.

Be Yourself, Be an ING'er

  • Welcome Leave: Enjoy 14 days of welcome leave, even in your first year
  • Career Opportunities: Self-driven career paths and international opportunities
  • Personal Growth: Challenging work and continuous development
  • Dynamic Environment: Informal, vibrant, and collaborative culture
  • Innovation Culture: Explore and apply PACE methodology
  • Global Exposure: Participate in international projects and communities
  • Communication & Celebrations: Various communication activities and celebrations
  • Health Care: Comprehensive private health insurance for you and your family
  • Private Pension Plan
  • Meal Card
  • Transportation Allowance
  • MultiSport Membership
  • English Language Development Support
  • Remote working opportunities throughout August

How to Apply

Click the application button on our careers page and submit your application through Workday.

About ING

With 65,000 employees and operations in approximately 40 countries, there is no shortage of opportunities for people with initiative who want to help people take a step ahead in life and in business.

Do you want to work at the cutting edge of what's possible and at the same time ensure you work with integrity and hold the customer's interests at heart? Do you want to be surrounded by progressive, inspiring, diverse and supportive colleagues?

Then there is no better place to invest your talents than at ING.

Join us. Apply today.

About ING Hubs

Following ING's strategic ambition to deliver a superior experience to its customers worldwide, the hubs network contributes to fostering efficiency and digitalization across ING. Providing concentrated expertise along with scalable and sustainable solutions, the hubs focus on straight-through processing, delivering automated services like software development, data management and retail operations.

Present in Poland, Romania, Slovakia, the Philippines, Türkiye and Spain, ING Hubs employ more than 13,000 professionals in domains such as software development, data management, operations and non-financial risk.

Discover ING Hubs Türkiye

ING Hubs Türkiye is looking for talents to join an international network of professionals. Building on an existing framework and shared mission, our up-and-coming team will bring its unique personality and skills set to provide borderless services with bank-wide capabilities.

We value strong work ethics, knowledge sharing and flexibility in our way of working - it is both our promise to you and what we look for in new colleagues.

Let's meet!

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