Enjoy working in a fast pace, collaborative environment across multiple quantitative functions of the Treasury Group.
Work closely with equity financing desk and other treasury teams to manage key mandate, translating business specifications into data-driven analysis and models, creating automated reporting. Such analysis and models will leverage both internal and external data sets, targeted product suite include counterparty performance analysis, market colors, security financing trend lookback and look forward, refinance opportunity radar.
Work with key stakeholders, including Treasury, Operations and Technology, to develop, implement, review and deploy the aforementioned models and reports into the firm’s infrastructure.
Build equity finance data sets and assist to integrate the data into the global treasury quantitative ecosystem. Assist in the development of a systematic process for cost efficient allocating Millennium’s multi-asset portfolio across various equity financing counterparties and products within the region.
Assist in the development of a quantitative framework for allocating financing charges to relevant portfolio managers.
Responsibilities
Collaborate with quantitative modellers in the development of comprehensive and dynamic model (suite of models) for cost efficient portfolio optimization and allocation across multiple Financing Providers.
Work independently to translate specific user requirements into quantitative models and automated reports. Collaborate with the Technology team to push these models and reports into production.
Work with team members to consume and analyze prime brokers locate and fulfil data, this requires intimate knowledge of stock borrow and loan, related pricing and billing terms, commonality and differences in cash PB and swap PB products, market specific restrictions on short selling and stock covering.
Own and drive development of statistical models to classify vendor’s capacity to cover and relative strength in pricing, track security’s cost to finance and model the best allocation strategy to lower overall cost and better sustainability of coverage. High quality counterparty analysis could be integrated to counterparty score card.
Prepare formal documentation of all models and processes in which the individual is involved.
Qualifications/Skills Required
Degree in a quantitative discipline (e.g., Engineering, Statistics, Mathematics, Physics or Computer Science) and hands-on working experience with data analysis.
Interest in the financial markets and hedge fund trading strategies (across all major asset classes)
Ability to work independently and with minimal supervision.
Strong knowledge of SQL and at least one high-level language for quantitative modelling - Python preferred.
Good oral and written communication skills.
Prime Brokerage (stock loan in particular) and multi-asset class knowledge is a plus.
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