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    Quantitative Engineer - London, United Kingdom - Goldman Sachs

    Goldman Sachs
    Goldman Sachs London, United Kingdom

    1 week ago

    Default job background
    Full time
    Description
    Solve the most challenging and pressing engineering problems for our clients.

    Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action.

    Create new businesses, transform finance, and explore a world of opportunity at the speed of markets .
    The Controllers division is responsible for financial control and regulatory obligations of the firm.

    They safeguard the assets of the firm through an independent scrutiny of the financial information and ensure accurate reporting to internal and external consumers.

    They provide critical metrics and related analysis to the firm's and divisions' leadership to navigate the evolving business strategy, including incumbent and strategic initiatives.

    Controllers play an important role in the changing landscape of the firm, including its new business ventures and acquisitions, and ensure that these new initiatives are in line with the regulatory expectations as well as controlled in terms of their incorporation into the firm
    Finance engineers help ensure the firm meets all of its financial control and reporting obligations.

    Working in small and nimble teams, we build critical and complex software to calculate profit and loss (P&L), independently verify valuations, measure and optimize the firm's capital, balance sheet and liquidity metrics, and regulatory filings across the globe.

    Finance Engineering is responsible for designing and implementing solutions to manage the firm's P&L, independently verify valuations, measure and optimize the firm's capital, balance sheet and liquidity metrics, and regulatory obligations.

    Our global agile teams (based across Americas, EMEA, and Asia) develop and manage the platforms, calculation engines, and analytical tools that controllers, risk management, and deal-making teams use to project, monitor and report externally to regulatory for both regular business activity and under stress scenarios.

    Our people must continually find new ways to provide access to capital, manage risk and provide investment opportunities for our clients to enable them to realize their goals.

    We judge ourselves on our ability to help clients anticipate and respond to changing market conditions and to create opportunities that merit the trust they place in us.

    Controllers Strats is a multidisciplinary group of quantitative experts within the Controllers Division, focusing on independent price verification, regulatory capital measurement, revenue analysis and modelling.

    The group is primarily responsible for building advanced quantitative models and analytical tools for valuation risk and regulatory capital pertaining to the three areas mentioned.

    Broad exposure to pricing and calibration models for a variety of financial products, including derivatives, illiquid cash products, private equity, etc.

    Exposure to challenging quantitative problems such as modeling risks for derivatives, large scale Monte-Carlo simulations of complete portfolios across the firm, fast and accurate approximate valuation risk measurements.

    Exposure to machine learning and data science skills, and applications in finance.
    Gain understanding of evolving regulatory framework and leverage quantitative skills to help the firm manage capital resources.

    Autonomy:
    You'll have significant autonomy in designing and writing solutions to help our stakeholders deliver for the firm's clients.

    Training:

    Your manager will support your professional development, allowing you time for training at work, helping you learn and grow within the organization, and providing opportunities for increasing responsibility.

    Independent price verification models that govern key business strategies and decisions related to valuation of products including complex derivatives and hard to value private investments
    Revenue analysis and modelling that governs new activity review, valuation adjustments and signoff of daily P&L for all of market making desks
    Regulatory Capital models for key externally reported capital metrics that play a key role in determining forward-looking business strategies and decisions in an evolving regulatory landscape

    Provide ongoing testing and support for existing models
    Documentation and quality control of models.
    Provide technical and functional guidance and leadership to junior members on a need basis
    PhD or Master's candidate in a quantitative field such as mathematics, physics, statistics or engineering
    ~2-4 years experience in financial modeling
    ~ Exposure to machine learning and data science skills, and applications in finance is a plus.
    ~ Strong programming skills and experience with an object oriented programming language (such as C++, Python, or Java).
    ~ At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world.


    We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

    We're committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Goldman Sachs is an equal employment/affirmative action employer Female/Minority/Disability/Veteran/Sexual Orientation/Gender Identity
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