Quantitative Research Analyst

continues to expand its fund offerings and remains a key growth area for the firm. We are seeking a quantitative analyst / desk quant to join our London front office trading analytics team to support this expansion and assist Portfolio Managers in their investment and asset management decisions. The London team covers a variety of asset classes, for US, Europe, and Asia, with a focus on asset-backed finance (ABF), performing and non-performing loans, SRTs, unsecured lending, and consumer credit asset classes. The focus of the role will be to perform initial value deal assessments via data analysis, modelling and pricing of fundamental risks, and relative value (across capital structures and asset classes) analyses. Post-trade support is also a fundamental consideration where we monitor and report on collateral and trade performance (surveillance). The chosen candidate will be highly technical and have a good understanding of asset pricing (including risk neutral, CAPM) theory

probability theory, and experience with key asset classes (namely asset-backed, credit, and/or rates). Ideally you will have a front office quant (sell or buy side) background and be proficient in developing new pricing models and implementing into Python code. An ability to develop new approaches to pricing bespoke transaction features is important, as is experience with working with, and contributing to, large coding infrastructures. Ability to work closely with Portfolio Managers and build strong relationships is highly desirable. Requirements Masters degree or PhD in Mathematics, Physics (non-experimental), Probability/Statistics, Engineering, or (Mathematical) Finance. Familiarity with asset-backed structured products, Intex and data analysis or empirical modelling is a strong plus. Minimum of 3 years of relevant professional experience at a top sell-side or buy-side institution in a front office quantitative role. Exceptional quant / analytical skills -
knowledge of advanced pricing techniques, asset pricing theory, probability theory, and cash flow / bond maths (e.g. OAS calculations). Experience designing, coding, and implementing pricing and surveillance frameworks for automation / streamlining of tasks. Strong coding skills in Python - candidates for whom Python experience is limited to occasional / hobby usage should not apply. Experience with structuring / liability-side (e.g. SPV mechanics) aspects of finance a big plus. Working knowledge of Linux/Unix/Bash and SQL would be a plus. Equal Employment Opportunity and Affirmative Action Statement PIMCO recruits and hires qualified candidates without regard to race, national origin, ancestry, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth, breastfeeding, or related medical conditions), sexual orientation, gender (including gender identity and expression), age, military or veteran status, disability (physical or

PIMCO is a global leader in active fixed income with deep expertise across public and private markets. We invest our clients' capital across a range of fixed income and credit opportunities, leveraging our decades of experience navigating complex debt markets. Our flexible capital base and deep relationships with issuers have helped us become one of the world's largest providers of traditional and nontraditional solutions for companies that need financing and investors who seek strong risk-adjusted returns. Since 1971, our people have shaped our organization through a high-performance inclusive culture, in which we celebrate diverse thinking. We invest in our people and strive to imprint our CORE values of Collaboration, Openness, Responsibility and Excellence. We believe each of us is here to help others succeed and this has led to PIMCO being recognized as an innovator, industry thought leader and trusted advisor to our clients. Job Description The alternatives business at PIMCO