Principal data scientist

ING Analytics is a unit responsible for realizing this vision for ING, differentiating ING as a leader in data-driven organization, within the banking sector and beyond. The team consists of a number of tribes around the bank’s key domains (such as Operations, Retail Banking, Wholesale banking, etc.), local country analytics teams, as well as strong support areas around data management, technology, customer journey, UX, and external partnerships.

We are incredibly excited about Analytics and the great potential for progress and innovation. We believe that analytics is a key differentiator in bringing superior customer experience.  We wish to improve our operational processes and create new and innovative data-driven products that go beyond traditional banking, such as the platform models.

Retail Banking Analytics Team

The RBA Team provides ING with machine learning expertise for the development of the credit acceptance, pricing, personalization (incl GenAI), and marketing (for example churn prediction). We are based in Amsterdam and consist of two teams with a total of 14 highly-skilled and talented data scientists from diverse nationalities and backgrounds (such as physics, statistics, computer science or artificial intelligence). We work in a fun and creative environment, and we are dedicated to bringing out the best our projects  and in each other and through collaboration and knowledge sharing. The portfolio of projects is broad and uses a wide range of algorithms and tools. In short, we offer a world-class working environment for data scientists to make an impact and never stop learning.

What You’Ll Do

As a Principal Data Scientist, you will be

• Designing and developing machine learning solutions for specific business use cases.
• Leading the data science solution for multiple projects.
• Doing stakeholders management.
• Collaborating with subject matter experts and machine learning engineers to bring your advanced models to production.

Who Are You?

• You are highly motivated when solving complex problems and have an always-learning attitude. You keep on top of the latest developments in machine learning and apply them in your projects where they bring value.
• You enjoy sharing knowledge with your teammates and helping others improve alongside you.
• You have a solid and broad background in machine learning, especially in classification and regression.
• You enjoy coding. You have excellent Python and software engineering skills, and you know the linux shell. You also master git for version control and SQL dialects for interacting with databases.
• Willingness to learn: you are self-reflective and open to constructive criticism on both the technical and interpersonal level.

Required Skills

• Extensive theoretical knowledge of statistical modelling and machine learning, and a demonstrated ability to apply these to solve business problems and develop innovative models and/or data-driven products.
• 7+ years of work experience in the data science field in the financial sector. Knowledge of lending, credit risk, and credit decision domains is a strong plus.
• Hands-on experience with the development and implementation of GenAI solution in the financial sector.
• Senior software engineer level programming skills including mastering Python, Spark and git versioning. Excellent knowledge of data engineering and DevOps.
• You have a very solid educational background that includes mathematics and statistics.
• You have excellent written and oral communication skills in both technical and business contexts.
• Fluency in spoken and written English.

What We Offer

• An opportunity to become part of an international and ambitious team of highly-skilled, talented people who love working collaboratively.
• A full-time position (40 hours / week).
• An excellent package including 13th month, holiday allowance, and personal choice budget.
• A very stimulating intellectual environment as part of the international ING Analytics community.
• Exciting, impactful and highly-visible projects in a global organization where advanced analytics are a strategic priority.
• A MacBook Pro, plus an allowance for a work mobile and your home office setup for our Hybrid Mode way of working.

About ING’s Think Forward strategy

ING’s purpose is to empower people to stay a step ahead in life and in business. Our strategy is built around our purpose and making the difference for people and the planet. We are an industry recognized strong brand with positive recognition from customers in many countries, a strong financial position, omni-channel distribution strategy and international network.

If you want to work at a place where we believe that you can make the difference by using machine learning to generate data driven products and solve the most pressing business challenges, then this position is for you.

Rewards & Benefits

We want to make sure that it’s possible for you to strike the right balance between your career and your private life. You can find out more about our employment conditions at http://careers.ing.com/en/benefits-NL

The benefits of working with us at ING include:

• Hybrid working mode (flexible working from home and office)
• 24-27 vacation days depending on contract
• Pension scheme
• 13th month salary
• Individual Savings Contribution (BIS), 3.5% of your gross annual salary
• 8% Holiday payment
• Personal growth and challenging work with endless possibilities
• An informal working environment with innovative colleagues
• Work Agile, so new ideas come to life faster

About Ing

With 60,000 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.