Quant Analyst - Predictive Analytics for IT Portfolio Optimisation (3530)

Zürich  ‐ Vor Ort
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Beschreibung

For a 6 months project at our client site in Zurich, an international bank, we are looking for an experienced

Quant Analyst - Predictive Analytics for IT Portfolio Optimisation (3530)

The ideal candidate knows Top-down portfolio optimisation reviews, can provide independent validation, optimisation and challenge of proposed business cases. Knowledge in spectral clustering, principlal component analysis, dependent structures, machine learning (quantitative technique) would be a big advantage.

Your qualifications:

Multi-year experience in business analytics, portfolio optimisation or research role in banking
Strong analytical, numerical and problem solving skills
Ability to understand complex issues and explain them in simple terms
University education with research background, preferably in finance, science, or engineering
Strong IT skills, proficient user of MS office programmes, especially Excel and Powerpoint
Possess strong commercial acumen, as well as knowledge and understanding of the banking business and environment
Team player and proven ability to lead virtual teams
Excellent command of English (both written and verbal)
About the role:

The simplification of IT application portfolios is one of the major strategic investments at our client
Use predictive analytics to systematically identify and advise on simplification opportunities across the whole IT portfolio
Provide an integrated view of financial analysis combined with IT architecture degrees of freedom
Identify headwinds together with the CTO organisation and ensure that simplification actions do not hurt economically profitable businesses
Categorise business cases into high and low priorities
Are you ready for a new challenge and available in February 2016 on site in Zurich? We look forward to receiving your application in MS-Word on If you have any questions, don’t hesitate to call us in Zurich: .
Start
02.2016
Dauer
6 Monate
Von
iET SA
Eingestellt
12.01.2016
Ansprechpartner:
Senior Recruiter
Projekt-ID:
1049886
Vertragsart
Freiberuflich
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