Lead Data Scientist- Financial Crime & RegTech

Deze vacature is niet meer vacant

Data Science Chapter Lead – Financial Crime

Location: Amsterdam

Job type: Full Time position

The opportunity

ING’s goal is to enable people to “do their thing” and empower them to stay a step ahead in life and in business. We are one of the largest banks in Europe and we continuously evolve to become one of the most innovative companies in the banking sector.

The ING Analytics group is a major driving force in ING’s transformation, aimed at helping us to become a data-driven digital leader and creating tangible value for ING and its customers through world-class analytics products and services.

The team

In our ING Analytics for KYC (Know your customer), Fraud and Cybersecurity Tribe, we are passionate about creating advanced analytics applications to mitigate the risk of financial, economic crimes (FEC) for our society, and about delivering models and products across multiple countries and domains, making ING a safer and more compliant bank. This is a diverse international group which combines data, IT, and product management roles in interdisciplinary squads, and we strive to push the boundaries of utilizing our big and sensitive data sources with statistical and machine learning understanding to tackle important challenges, such as anti-money laundering (AML), counter-terrorist financing (CTF), post-transaction monitoring (PTM) and customer due diligence (CDD).

Roles and responsibilities

As we continue our growth and establishing the added value analytics bring to our domain, we seek a team/chapter leadership profile which can lead a small (5-8) group of data scientists. As a data science chapter lead, your role will have four (4) main aspects:

  • As a member of your chapter , you will act as a senior data scientist as part of a model/product building squad. You will work on a financial crime use case, applying statistical, data science and machine learning approaches. This will assume 50% of your role scope.

  • As the lead of your chapter, you are the direct manager of the data scientists in your chapter. You will drive the skills and career development of your chapter members, set targets, and evaluate their performance in squads, providing feedback and guiding them technically and professionally.

  • As a part of the tribe’s management team, you are responsible for the success of the tribe with various activities, recruitment, ranging from setting standards for model development, staffing squads with talent from the tribe, setting up non-financial risk (NFR) controls, reviewing squad progress and providing feedback.

  • As a leader in the wider ING Analytics community , you will be a part of a wider group of chapter leads who drive the development of ING Analytics for all its members and take on activities such as forming and building professional guilds and meet-ups, specifying requirements for platform teams, optimizing processes for obtaining data and model validation, and engaging with senior stakeholders to realize the transformation of ING with advanced analytics.

How to succeed

We hire smart people like you for your potential. Our biggest expectation is that you’ll stay curious. Keep learning. Take on responsibility. In return, we’ll back you to develop into an even more awesome version of yourself.

At ING, we promote diversity not just because it is the right thing to do, but because it is essential for delivering on our strategy. To stay a step ahead we need teams with a healthy mix of contrasting perspectives and backgrounds as they are more creative, faster to adapt to and more inventive with their solutions. We strive to hire a workforce as diverse as the communities in which we operate, and we will consider every application, regardless of race, religion, color, national origin, sex, disability, or age.

If you are an experienced senior data scientist / machine learning developer (5+ years), or you are currently leading a data science team (1+ years) and are looking to lead a talented group tackling one of the most meaningful and important domains in FinTech today, we would love to hear from.

Additional optional criteria which will be considered separately as a “plus”:

  • Prior experience in either the KYC, anti-money laundering (AML) or Anti-Fraud domains.

  • Strong python development skills and python-specific best practices knowledge.

  • Specific experience in the fields of either: outlier detection, representation learning or graph analytics.

  • Proven leadership experience.

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 https://www.ing.jobs/netherlands/Why-ING/benefits.htm

The benefits of working with us at ING include:

  • A salary tailored to your qualities and experience

  • 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


Contact Robin Heerma in our recruitment team (robin.heerma@ing.com) for more information about this role. Want to apply directly? Please upload your CV and motivation letter by clicking the “Apply” button.

About us

With 57,000 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.

Vacature informatie

Organisatie: ING

Locatie: Amsterdam

Opleidingsniveau: WO

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