Quant Guide 2020: University of Washington

Seattle, US

QUANT 32 University_of_Washington_Quad_cherry_blossoms_2017-20-web.jpg

Many quantitative finance master’s programmes aim to be closely aligned with industry practice. The University of Washington can argue its MS Computational Finance and Risk Management programme has made advances in this area after the number of course instructors with an industry affiliation increased from five last year to nine in this year’s Risk.net quant guide.

Curricular changes have taken place too, says programme manager Laurie Feldman. Updates include a new course on financial technology, blockchain and cryptocurrencies, plus the introduction of a financial data analytics graduate-level certificate. The certificate is earned online and requires students to tackle work from several related degree modules, including financial data science and machine learning for finance.

The master’s programme comprises seven compulsory courses and a smaller number of electives. One of the core courses is, unusually, ethics in finance, which includes material involving financial law and regulation as well as ethical problems and case studies. Among the electives are a master’s thesis, an independent study project and an industry internship. The thesis, according to the programme, is recommended for students who aim to pursue further study following completion of the master’s.

Over the last few years of the programme, Feldman says, growing numbers of students have been taking part in research projects, internships and hackathon events with fintechs. But career routes remain “steady”, she adds; a majority of graduates take up positions in commercial banking and portfolio management, while some have also gone into policy-related roles at public bodies including the Federal Reserve. The programme reports a 93% employment rate in finance roles six months after graduation.

View this institution’s entry in the 2019 guide

View other universities and a guide to the metrics tables

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