Internal Audit Off-cycle Internship
- Budapest
- Tréning/gyakorlat
- Teljes munkaidő
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kérjük add meg a következő adataidat:E-mail cím:Vezetéknév:Keresztnév:RegisztrálokBezárásInternal Audit Off-cycle InternshipDuring this internship you will have the opportunity to gain insight into the world of investment banking while taking part in protecting the Firm against major risks. You will join the Model Audit Group within the Budapest Internal Audit organization and can work in a flexible work arrangement, 20-40 hours per week.We offer:
- A supportive and dynamic multinational environment within an inspiring international team
- Continuous development opportunities and access to comprehensive training tools
- An introduction to Morgan Stanley and a deep dive into how technology drives the investment banking business
- Participation in the firm's networking events
- Flexibility and opportunity to work from home
- Internship extension / Full-time offer upon graduation
- Learn about a large variety of financial mathematical models used across the Firm (e.g. derivatives pricing, risk management, stress testing, capital planning and decision-support models)
- Gain an understanding of processes, risks and controls within the model development and usage framework of a global financial service company
- Assist in the quantitative review of models and regularly monitor model performance, including an assessment of the model development and validation process, the methodological basis and data usage of models
- Cooperate with other audit groups and internal stakeholders to identify weaknesses or vulnerabilities of the models and the model development process
- Learn about a large variety of data analysis and data visualization tools and techniques which are used across the Firm (e.g. Python, QlikView, Tableau, Alteryx)
- Develop data solutions and generate insight from large and multiple sources of data for the Banks Internal Audit dept assurance activities.
- Collaborate with colleagues in the preparation of reports with key messages about specific risk indicators and metrics.
- Contribute ideas on how (new) data techniques can be applied to improve efficiency and effectiveness of audit processes.
- Ongoing studies (BSc or above) in Programming, Mathematics, Physics, Finance or Economics, Data Science, Data Engineering, or similar field
- Quantitative background, good analytical and numerical skills, or background in one of the widely used programming languages for data analytics (Python, R or similar)
- An understanding of quantitative finance and financial mathematical models is a plus
- Experience in data visualization tools such as Tableau or QlikView is a plus
- Fluency in English, both verbal and written
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