Senior Data Scientist – Cyber Risk Analytics
ING is hiring a Senior Data Scientist – Cyber Risk Analytics. Level rates it ; you can apply on ING.
Level's read on this job
- Builds AI ●●●● is how Level rates this data scientist role: the job is building AI systems.
- Tools and skills the posting cites include MLOps and AI evaluation.
- Level classifies it as a senior role.
- Level lists 707 other open roles at ING.
- The role was posted in the last few days.
AI in this role
At ING Hubs Spain we are looking for a Senior Data Scientist – Cyber Risk Analytics
Your role and work environment:
We are looking for an experienced Data Scientist to join our Security Analytics team, with a dedicated focus on Third-Party Cyber Risk Management (TPCRM). The role will be responsible for designing, developing and operationalising advanced analytical, machine learning and AI-driven solutions that strengthen our ability to assess, monitor and anticipate cyber risks associated with third-party vendors.
A key initial focus will be the development of continuous risk models and dynamic vendor risk scoring, moving beyond periodic assessments towards more proactive, data-driven risk management. Working closely with TPCRM specialists and other cybersecurity stakeholders, you will take end-to-end ownership of an expanding portfolio of analytical and AI solutions, from initial design and development through to deployment and continuous improvement.
Your key responsibilities:
As a Data Scientist you will:
- Design, develop and maintain AI models to quantify, assess and monitor third-party cyber risk.
- Develop dynamic vendor risk scoring capabilities by integrating multiple internal and external data sources, including risk assessments, security posture indicators and threat intelligence.
- Identify opportunities to apply predictive analytics, anomaly detection and other advanced analytical techniques to improve risk identification and prioritisation.
- Explore and develop agentic AI solutions, leveraging large language models (LLMs), tool integration and automated reasoning workflows to enhance risk assessment, intelligence gathering and decision support.
- Take end-to-end ownership of the model lifecycle, including data preparation, feature engineering, model development, validation, deployment, monitoring and recalibration.
- Collaborate with TPCRM specialists, cybersecurity teams and data engineers to translate complex risk challenges into scalable analytical solutions.
- Ensure models are robust, explainable and aligned with internal model governance, data quality and regulatory requirements.
- Communicate analytical findings, model performance and risk insights effectively to technical and non-technical stakeholders.
- Continuously identify and develop new data science use cases to enhance third-party cyber risk management capabilities.
What are we looking for?
Want to know if this job is made for you? These are some of the qualities that we value the most for this role. And if the shoe fits… don’t hesitate to apply!
- Master’s degree or PhD in Data Science, Computer Science, Statistics, Mathematics, Physics or a related quantitative discipline.
- 7+ years of professional experience in data science, advanced analytics, statistical modelling or machine learning, preferably with experience delivering solutions into production.
- Familiarity with generative AI, LLM-based applications and emerging agentic AI architectures, including their practical applications and limitations
- Strong proficiency in Python and SQL, including hands-on experience with common data science and machine learning libraries.
- Proven experience developing, validating and maintaining statistical and machine learning models throughout their lifecycle.
- Strong understanding of statistical methods, predictive modelling, feature engineering, model evaluation and uncertainty.
- Experience working with complex, heterogeneous datasets and translating ambiguous business problems into structured analytical approaches.
- Familiarity with model deployment, monitoring, reproducibility and MLOps practices.
Ability to independently lead technical initiatives while collaborating effectively with multidisciplinary teams.
- Strong analytical, problem-solving and communication skills, with the ability to explain complex modelling approaches to non-technical audiences.
Preferred Qualifications
- Experience developing and deploying AI solutions in heavily regulated environments, particularly financial services.
- Familiarity with cybersecurity concepts, cyber risk management, third-party risk management or cyber risk metrics (preferred).
- Experience with risk scoring methodologies, probabilistic modelling, anomaly detection or decision-support systems.
- Familiarity with model risk management, explainability, regulatory expectations and governance frameworks.
- Experience with cloud-based data and analytics platforms and production-grade data pipelines.
What do we offer?
The time you spend at work, the challenges you face or the lessons you get are very important, but… What about your personal life? At ING we want your work to fulfill you in every way, and that is why we take care of even the smallest details.
Check out what is waiting for you!
Be flexible my friend.
Our model is all about flexibility and accountability. Keeping both our customers and our colleagues needs in mind, you determine together which days you work at home and which you come to ING MAD to offer your best self. Do your thing.
Restaurant card.
So that thinking about what to have for lunch doesn’t take up your time or your cravings.
Our house will be your home.
In our offices you can find electric mobility solutions, doctor, hairdresser, gym, The Good Service (to help you with your errands) and much more!
Health insurance.
For you and all your family (spouse/partner and children).
Life insurance.
We help you protect what matters most to you.
Flexible remuneration.
In addition, you will enjoy our flexible remuneration model, through a more tax-advantaged way, you will be able to access other services such as nursery, transport card, training aids…
Transport allowance.
It doesn't matter where you live, we’ll help you get to the office.
Pension plan.
You can benefit from our pension plan after 1 month with us!
Discover ING Hubs Spain
We’re building something exciting—and we want you to be part of it.
ING is launching the new member of ING Hubs in Spain, an integral part of ING in charge of designing and delivering important technological and operational solutions to make banking frictionless for our customers. ING Hubs play a key role in our ‘Growing the difference’ strategy to become the best European bank. This will be our sixth global hub, joining a network of over 13,000 professionals in the Philippines, Poland, Romania, Slovakia, Türkiye and Spain.
What makes us different?
We have a tech-first mindset: We’re not just a bank—we’re a tech company that happens to do banking. Our new hub will be a center of excellence for scalable, fast, and secure technology.
We have global impact: You’ll be working on solutions that serve more than 34 million of customers in over 38 countries.
We are agile: ING was the first bank to adopt agile at scale. We continue to evolve with a collaborative, cross-functional way of working.
Sustainability at the heart of what we do: We have a role to play in defining new ways of doing business that align economic growth with positive environmental and social impact.
At ING, we believe in diversity, inclusion, and belonging. We’re proud of our international teams and are committed to creating an environment where everyone can thrive. We value authenticity, collaboration, and continuous learning.
We’re looking for curious minds, bold builders, and passionate problem-solvers. If you’re looking for a place to find new ways to drive efficiency and provide superior customer value, where your ideas matter, and where you can grow with purpose—we’re looking forward to meeting you.
How we rate this
Senior Data Scientist – Cyber Risk Analytics at ING rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data scientist jobs at this level
Pay
- Typical data scientist job
- $167k
This posting doesn't list pay. Use the typical data scientist figure when pay comes up. See data scientist jobs
Questions you could be asked
- How do you monitor a model once it's live, and how do you know it needs retraining?
- How do you decide that one model's output is better than another's for a given task?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: ML Ops and AI Evaluation. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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