applied data science for banking and finance

The Master of Science in Applied Data Science for Banking and Finance is a two-year study program, utterly taught in English, conceived for students who aim at developing operative skills to cope with the new challenges that financial systems and their actors (e.g. financial intermediaries, investors, and regulators) face in the presence of the massive wealth of available data on market-relevant quantities.
Nowadays, digital technology empowers storage and processing of large amounts of data. However, data is not information and information is not always insight. The Master Program fosters flexible professional profiles capable of:
- managing large financial/banking/insurance data bases;
- filtering significant information out of conspicuous and heterogeneous data sets;
- extracting from massive data insights relevant to several decision-making processes in the financial industry (e.g. asset allocation, risk management, and client profiling/servicing).
The flexibility of the Master in Applied Data Science for Banking and Finance allows students to tune their study plans according to personal interests and bachelor backgrounds to solidly strengthen their skills in data science and machine-learning technologies, quantitative methods for finance, financial intermediation and banking, in empirical analysis of investment strategies, and in regulation.
The teaching calendar is organized in two 6-month terms.
Applicants who are non-native speakers of English must provide evidence of English language proficiency. For any further information, please refer to the graduate program website.
Attendance to the lectures and laboratory activities is strongly recommended.