ING Hubs Spain Data Scientist interview questions & guide 2026

As a Data Scientist at ING Hubs Spain, you are at the intersection of advanced technology and global finance. Your work directly influences how ING secures its systems, optimizes operations, and delivers frictionless experiences to over 34 million customers across 38 countries. This role is not just about building models; it is about translating complex, large-scale data into actionable intelligence that protects the bank and empowers decision-makers.

You will join a culture that prides itself on a "tech-first" mindset. Whether you are working within Global Threat Management (GTM) to detect cyber threats or optimizing product metrics, you will be expected to balance technical innovation with rigorous governance and explainability. The environment is fast-paced, collaborative, and deeply rooted in agile methodologies, meaning your ability to communicate analytical outcomes to both technical and non-technical stakeholders is as critical as your coding proficiency.

The following questions reflect the patterns observed in real interview loops at ING Hubs Spain. While specific questions will vary based on your team and seniority, focus on mastering the underlying concepts rather than rote memorization.

Product Sense and Metrics

• How would you define the success metrics for a new digital banking feature?
• If you noticed a sudden 10% drop in active users for a specific product, how would you diagnose the root cause?
• How do you balance short-term product engagement with long-term security and stability?

Preparation at ING Hubs Spain requires a blend of rigorous technical application and a clear, product-oriented mindset. You must demonstrate that you can move beyond theory to deliver operational impact.

Technical Competency – You will be evaluated on your ability to write clean, efficient code and apply machine learning models to real-world problems. Be prepared to discuss your choice of algorithms and how you ensure their explainability.

Analytical Problem-Solving – Interviewers look for how you structure ambiguous problems. Use frameworks to break down large, messy datasets and explain your logic clearly as you iterate toward a solution.

Communication and Influence – Your ability to articulate the "why" behind your data is crucial. Practice translating technical findings into business language that helps stakeholders make informed decisions.

Cultural Alignment – ING Hubs Spain values collaboration, ownership, and an agile mindset. Demonstrate that you are a team player who can navigate cross-functional environments and adapt to changing priorities.

The interview process at ING Hubs Spain is designed to be thorough but professional, typically spanning several weeks. It generally begins with an HR screening call to assess your background and motivation. This is followed by a technical stage, which may include an online assessment, a take-home challenge, or a technical interview focusing on statistics and coding.

Final stages involve meeting with hiring managers or product owners to discuss your past projects and your approach to the case study or technical assessment. The process is structured to test your skills in increments, allowing you to showcase your depth of knowledge and your ability to work within the ING ecosystem.

The visual timeline above captures the typical progression from initial screening to final interview rounds. Use this to pace your preparation, ensuring you dedicate enough time for both coding practice and deep dives into your own past projects.

Experimentation and Metrics

Success in this role depends on your ability to design robust experiments and interpret metrics. You will be evaluated on your grasp of statistical significance and your intuition for avoiding bias.

Be ready to go over:

• A/B testing design and power analysis.
• Metric drop diagnosis using funnel analysis and cohort tracking.
• Experimentation pitfalls like selection bias, novelty effects, and sample ratio mismatch.
• Advanced concepts: Multi-armed bandit testing and sequential testing methods.

SQL and Data Engineering

Data is the lifeblood of ING. You must demonstrate proficiency in manipulating large datasets to extract meaningful features for your models.

Be ready to go over:

• SQL window functions (e.g., RANK, LEAD, LAG, SUM() OVER).
• Query optimization techniques for large, distributed databases.
• Data cleaning and handling of outliers in security-related datasets.

As a Data Scientist at ING Hubs Spain, your day-to-day will involve transforming raw, large-scale data into actionable intelligence. You will collaborate closely with cyber threat hunters, product owners, and engineering teams to operationalize your models.

Your work will include:

• Designing and deploying machine learning models to identify, prioritize, and investigate threats.
• Building data pipelines that handle diverse, and often imperfect, security telemetry.
• Presenting analytical outcomes to stakeholders to influence the bank's defensive posture.
• Participating in agile ceremonies, contributing to a culture of continuous improvement and knowledge sharing.

A strong candidate for this role possesses a mix of technical rigor and business acumen.

• Must-have skills: Proficient in Python and SQL, strong understanding of statistics, experience with machine learning frameworks, and the ability to work with large-scale datasets.
• Nice-to-have skills: Experience with cloud platforms (e.g., Azure/AWS), knowledge of cybersecurity principles, and advanced certifications in AI or Data Science.
• Soft skills: Excellent English communication (B2 level or higher), ability to influence stakeholders, and a collaborative, "can-do" attitude.

Q: How long should I spend preparing for the technical assessment? A: Dedicate at least 1–2 weeks to brush up on SQL, statistics, and common machine learning approaches. The assessments often require a mix of theoretical knowledge and practical coding.

Q: What is the most important trait for a candidate to show? A: Beyond technical skills, show that you are an "outcome-focused" problem solver. ING values people who can connect their data work to real-world business impact.

Q: Is the interview process mostly remote? A: Yes, many interviews are conducted via digital platforms, though you should be prepared for the possibility of onsite components depending on the specific team and location.

Q: How do I handle the case study presentation? A: Focus on your methodology and your ability to defend your decisions. Expect challenging questions—treat them as a collaborative brainstorming session rather than a confrontation.

• Structure your answers: Use the STAR method (Situation, Task, Action, Result) for behavioral questions to keep your responses concise and impactful.
• Show your work: During coding or case study rounds, talk through your thought process. Interviewers are as interested in how you think as they are in the final answer.
• Know the business: Familiarize yourself with how ING Hubs functions as a global network. Understanding the "Growing the difference" strategy will help you frame your answers with the right context.
• Be ready for ambiguity: Real-world data is rarely clean. When asked about a project, highlight how you dealt with imperfect or missing data.

The Data Scientist role at ING Hubs Spain offers a unique opportunity to apply advanced analytics to global-scale challenges. By focusing on your technical foundations in SQL and statistics, while simultaneously practicing how you communicate your product impact, you will be well-positioned to succeed.

You can explore additional interview insights, practice questions, and preparation resources on Dataford to further refine your strategy. You have the skills and the drive to contribute to a world-class team, so approach your interviews with confidence and clarity.

The compensation data provided represents the broad range for this role, reflecting variations in seniority, location, and individual experience. Candidates should consider the total rewards package, including flexible remuneration, pension plans, and other company benefits, as part of the overall value proposition.