At a glance

ABN AMRO Clearing N.V. (AACB) is looking for a data scientist to join the Global Finance Data Science team. Do you want to be working in an ambitious data science team covering the financial markets and the clearing industry in an international environment? Thanks to our global network with offices in eleven countries and proximity to all major exchanges, you will serve the best trading firms on four continents.

Your job

As a data scientist you will work on multiple projects and do this with other Data Scientists in the team, where you will often take a leading role. Although we are part of the Global Finance department, our projects extend beyond the finance domain. For example, you will collaborate with colleagues from departments such as risk, operations, and commerce. In your work you will take care of the full development cycle. This includes the following topics:

• Identifying and exploring new opportunities, including experimentation with prototypes. 
• Building explanatory (time series) models for data-driven business understanding and decision making. Examples are driver analyses for cleared volumes or pricing analysis.  
• Building predictive / forecasting models. Examples are liquidity and trade volume forecasting.
• Building data pipelines of which the output can be used for our team (e.g. for feature engineering, or directly as input for models) or for colleagues to build dashboards on.
• Ad-hoc statistical analysis for senior management.
• Stakeholder management to make your projects a success, where stakeholders could be based in one of our offices in APAC, Europe, the US, or Brazil. 
• Presenting your end-to-end data science solutions to a broad non-technical audience.
• Translating business use cases where we can apply innovative models such as GPT/large language models. 

The aim is to put models to production and for this we have supporting infrastructure to do so. With 6.2 billion transactions being cleared annually and with peak volumes of up to 51 million transactions per day, ABN AMRO Clearing produces a lot of data. In other words, lots of possibilities to do relevant and meaningful work for a data science professional. 

Working environment

ABN AMRO Clearing is the cornerstone of global financial markets. We are a globally active multi-asset prime broker, custodian and general clearing member (GCM). We provide execution services, clearing, settlement, custody, securities lending, reporting and financing services for listed derivatives, cash securities, over-the-counter (OTC) products, exchange-traded funds (ETFs), commodities and foreign exchange transactions. We provide services from our offices across Europe, Asia-Pacific, Brazil and the United States. Our coverage includes all major exchanges and execution venues. AACB enjoys market share of 20% or higher for many of the major exchanges on which it operates. As a result, AACB consistently ranks among the top three clearers in every time zone, based on turnover and market share. 

Positioning in the organization

You will be working in the Global Finance Data Science team in Amsterdam, reporting to the Global CFO, and closely co-operate with regional finance teams and other departments. We are a team of data enthusiasts, each with our own preferences and skills in the data science domain. With our diverse skillset, we strive for an open and supportive work environment that encourages professional growth and work pleasure. You will play a crucial role in our team as a technical lead in projects and as a mentor for our junior team members, offering you the opportunity to contribute your unique perspective and make your mark.

Your profile

We are looking for the following criteria, we do understand that your skills might differ depending on your working experience: 

• 4+ years of working experience
• MSc or PhD in STEM or related field
• Experience in applying ML and bringing ML models to production
• Experience in Python for (statistical) analysis, ETL, feature engineering, and other data science tasks
• Experience in SQL to access databases
• Ability to translate business opportunities to an end-to-end data science use case
• Ability to communicate your results and solution to a broad audience, such as C-level management, IT colleagues, and finance professionals.
• Strong interest and motivation to work in the financial markets
• Experience with Dataiku, Tableau, and AWS is a plus
• NL based

Knowledge about financial products and the financial markets is needed to do the job. Don’t worry if your knowledge level is limited on these topics, we will provide training covering all essential information.

We are offering

You will be able to gain a lot of knowledge of the financial industry and products and also further develop your data science skills. We offer you excellent terms of employment and benefits:

• A salary in hay level 10 or 11, depending on level of experience (ranging from €4.800 - €7.850 per month, based on 40 hours)
• An additional benefit budget of 11%, with which you can buy flexible terms of employment
• A personal development budget of € 1,000 per year
• An annual public transport ticket for unlimited travel
• A good pension scheme
• A position that offers a lot of opportunities for professional development
• The ability to work flexibly
• Interesting work and challenging projects in an international environment

Equal opportunities for all

The success of our organisation depends on the quality of our people and the ideas that they have. Truly surprising insights and innovative solutions for our clients result from an interplay of cultures, knowledge and experience. Diversity is therefore extremely important to our organisation. To ensure that everyone at ABN AMRO can develop their talents, we encourage an inclusive culture in which all colleagues feel engaged and appreciated.

Disclaimer external recruitment agencies

External recruitment agencies need to have a signed agreement with ABN AMRO BANK N.V., executed by a Talent Acquisition Specialist, when submitting a resume to a vacancy. No unsolicited services or offers, please.