Data Analyst with strong Data Scientist skills

You will be involved in projects related to credit acceptance, personalisation, transaction categorization and pricing. You will have a hybrid role doing working mostly as an analyst and sometimes as a data scientist. As analyst, you will use your analytical and communication skills to optimize product funnels, develop complex reports, design and analyse A/B testing or generate other business insights. As data scientist you will develop full modelling pipeline using tree-based approaches. You will be part of a team with highly skilled and motivated colleagues, take ownership of your tasks and interact with fellow team members by sharing knowledge and experience.

The team
The Retail Banking Analytics (RBA) Chapters provides ING with expertise for analytics lending, pricing and personalization. We are based in Amsterdam and consist of 15+ highly-skilled and talented Data Scientists from diverse nationalities and backgrounds. To create more impact, we are extending our team with motivated Data Analysts.

We work in a fun and creative environment, and we are dedicated to bringing out the best in both each other and our projects through collaboration and knowledge sharing. The portfolio of projects is broad and uses a wide range of tools and solutions. In short, we offer a world-class working environment for data analysts and never stop learning.

Roles and responsibilities
As data analyst you will have a hybrid role. You will be the one extracting the business insights from the data but you can also be actively involved in the development of the full data science pipeline. You will collaborate with cross-functional teams, including product managers, engineers, marketers and data scientists. You will work on projects such as:   

• Credit acceptance modelling and funnel analysis

• Developping complex reporting tools covering the credit risk and collections funnels, including monitoring data quality and integrity

• Being part of the customer interaction team that develop propensity to buy models and design, implement and analyse A/B tests (and other experiment designs)

• Analyzing test results using statistical methods to derive actionable insights and make data-driven recommendations

• Presenting findings and recommendations to stakeholders in a clear and concise manner

How to succeed
We hire smart people like you for your potential. Our biggest expectation is that you’ll stay curious, keep learning and take on responsibility. In return, we’ll back you to develop into a better version of yourself. They keys for success are:

• You have strong background in statistics (for example a master in econometrics) and experience building classifiers based on boosting algorithms

• You have at least 4 years of experience in the financial sector. Domain knowledge in either credit risk, collections, pricing or marketing intelligence is a must.

• You are fluent coding in Python, Pyspark and SQL

• You have excellent communication and presentation skills

Rewards and benefits
We want to make sure that it’s possible for you to strike the right balance between your career and your private life. Find out more about our employment conditions.
The benefits of working with us at ING include:

• 25-28 vacation days depending on contract

• Pension scheme

• 13th month salary

• 8% Holiday payment

• Hybrid working

• Personal growth and challenging work with endless possibilities

• An informal working environment with innovative colleagues

About us
Curious about how ING empowers people and businesses to move forward?

Discover what we do and what we can offer you.

Questions?
Contact the recruiter attached to the advertisement. Want to apply directly? Please upload your CV and motivation letter by clicking the ‘Apply’ button.