Data Analyst (Risk Modelling) (Risk Hub) [rekrutacja online]
- You want to deal with data analysis and preparation in risk modelling (Credit and Market Risk).
- You want to work with global credit portfolio data.
- You like understanding and creating data requirements.
- You have min. 2 years of experience working in data analytics or data science.
- You know SQL.
- You have skills in business analysis for data requirements.
- You have experience in working with SAS and 4GL programming.
- You have higher education (preferably IT, quantitative/numerical, mathematics, physics, statistics).
- You are excellent team player, persistent, service oriented, customer centric, eager to learn.
- You feel a personal responsibility for the quality of your work and you work together with your colleagues across your domain.
- You would like to work in an international environment focused on creativity and modernity.
- You speak English on a good level.
- experience in modelling and machine learning,
- experience in working with credit and market risk modelling (PD, LGD, EAD, IFRS9, IRRBB),
- knowledge of Python and R languages,
- banking experience,
- knowledge of Agile / Scrum
- strong analytical, problem-solving, communication skills,
- an independent, creative and pro-active mind-set,
- the ability to challenge the status quo,
- great team player skills,
- high level of English
At ING Tech Poland and ING group we follow the Agile approach and mindset. We use flexible frameworks like Scrum and Kanban at our everyday work. We are innovative and we trust people we work with. The broad autonomy our employees have, stimulates motivation and creativity what allows us to adapt to the changing requirements of business partners. Small units called squads are the core of our organization. They have clear vision of products, overcome challenges autonomously and based on team cooperation, work out the most flexible and effective way of working.
Risk Hub Warsaw was created as a part of central risk team currently located in Amsterdam. In Warsaw we are building following chapters:
- Data and analytical engineering
- Credit Risk Modelling
- ALM Modelling
- Model Validation
- Modeling & Analytics (Tech)
We are new organization currently creating our work culture and way of working our task is to set new standards for entire risk team.
Within CRO Risk Service, the objective of the data and analytical engineering chapter is to automate, standardize, visualize risk data needed for the different risk modelling use cases by providing them fit for purpose data marts, analytical base tables and applications. We work as a crucial part of the Model Paradigm Shift program. Main products of squads lead by the chapter are new structural data delivery for modelling through analytical base tables and data mart and an application for automation of all model testing in development, monitoring and validation activities. People within automation and data squads cooperate with other cross chapter squads at RiskHub and Head Office in Amsterdam. In those squads colleagues from Data chapters help to better understand daily work challenges and how to optimize them.
- contract of employment
type of contract
- 8:00 - 18:00 (8 h)
- Zajęcza 4, Warsaw
this is the location of our office
- professional development
- certificates and knowledge development
- training budget
- access to the newest technologies
- international projects
- free English courses
- provate medical care
- 50% funded Multisport Card
- bicycle parking
- chillout rooms
- integration events and Stay Fit program
- stability of employement
- fully equipped workstations
Jeżeli w przyszłości, chciałbyś/chciałabyś brać udział w innych rekrutacjach prowadzonych przez ING Business Shared Services B.V. sp. z o.o. Oddział w Polsce z siedzibą w Katowicach, potrzebujemy Twojej dodatkowej zgody: „Wyrażam zgodę na przetwarzanie moich danych osobowych na potrzeby przeprowadzenia przyszłych rekrutacji.”
W przypadku wyrażenia zgody na przetwarzanie Twoich danych osobowych na potrzeby przyszłych rekrutacji informujemy, że będą one wykorzystywane przez okres 2 lat. Wszystkie informacje dotyczące przetwarzania Twoich danych osobowych znajdziesz tutaj.