Quantitative Consultant

How you
describe yourself

  • Master’s degree in econometrics, actuarial sciences, mathematics, physics or related studies
  • Experience with programming and analyzing large amounts of data using (e.g. Python)
  • A high problem-solving ability and able to distinguish main and side issues
  • You are enthusiastic about all the possibilities that big data offers
  • Excellent communication and writing skills in Dutch and English
  • You want to make an impact and contribute to a better world

What we
Offer

  • Challenging projects: you are in the lead to deliver success on great risk management projects
  • A horizontal organization where the lines are short and you can shape the strategy of the organization
  • Ample room and budget for personal development
  • A fantastic working location in the heart of Amsterdam
  • A great team of 60 smart, inspiring and sociable colleagues
  • Above market primary and secondary employment conditions

What you will do

We are looking for a Quantitative Consultant to help grow the firm. The job will require you to contribute to all phases of engagements, from origination to delivery, and participating actively in the office operations.

You will participate in various projects across our units and you will learn how to construct data solutions, which will be used for model development. Furthermore, you will learn how solutions and models are implemented in leading financial institutions in the Netherlands. In a short time you not only get to obtain in-depth experience in developing cutting edge machine learning models, you also actively work on implementing them at the clients. These models help financial institutions to detect fraudulent behavior and consequently make the world a better place.

You will learn fast and expand your skills by teaming-up with different clients and colleagues to solve challenging puzzles across different businesses.

Our company culture

RiskQuest is a consulting firm specializing in developing state-of-the art models and solutions for managing financial risks, preventing money laundering and terrorist financing, and making data-driven decisions to realize a sustainable strategy.

Since we were founded in 2008, we have been able to build and maintain an impressive customer base and work for all major Dutch financial institutions, including the Dutch central bank. We focus on our three pillars; Data Science, Financial Risk Modelling and Data Foundation.

The growing team consists of 60 exceptional quants with backgrounds in mathematics, physics, and econometrics, combined with a strong commercial sense and the ability to explain complex matters to management, development, and academic audiences.

Our beautiful office is located at the Herengracht in Amsterdam. The working culture is open and informal, we value entrepreneurship, and always thrive for the highest quality. There is an intense social life with daily chess matches, ping-pong competitions, after-work drinks, and regular trips.

Your day @ RiskQuest

  • Start of the day
    08:30 – 09:30
    After a beautiful bike ride through the city of Amsterdam to our office at the Herengracht. I start the day with a cup of coffee, having a chat with colleagues and checking my e-mail.
  • Meeting: Day Start
    09:30 – 10:00
    Time for the first meeting of the day, the day start. During this meeting we discuss the tasks that every team member is working on, together with general updates regarding the project. I ask a question related to a coding challenge that I am facing.
  • Coding
    10:00 – 12:00
    Time to do the real work and start working. Together with my colleagues we are working to extend the feature base for our model.
  • Lunch
    12:00 – 13:00
    Because we are located in the centre of Amsterdam there are numerous options to score a good lunch. Today I pick an option from our own ‘RiskQuest menu’, which is a list of the best places in the neighbourhood.
  • Stakeholder meeting
    13:00 – 14:00
    In the afternoon I have a more in-depth meeting with different stakeholders to discuss updates on important risk drivers for our model. We show how the newly created features provide more information about our target variable.
  • Ad-hoc analysis
    14:00 – 15:00
    Some analysis into the outcomes of some production models is required for management information.
  • Game of Ping Pong
    15:00 – 15:30
    When I am at the office at the Herengracht I always like to play a game of ping pong in our backyard. After a painfull loss against Emma, it is time to go back to work.
  • Finish up & organize code
    15:30 – 17:00
    Towards the end of the day, I clean up my code and push all my changes to GIT. After some final reviews I am ready to leave for home.

Apply now!