Senior Specialist, Model Risk (Machine Learning) 48 wyświetleń

ABOUT BNY MELLON
BNY Mellon is a global investments company dedicated to helping its clients manage and service their financial assets throughout the investment lifecycle. Whether providing financial services for institutions, corporations, or individual investors, BNY Mellon delivers informed investment and wealth management and investment services in 35 countries. As of March 31, 2021, BNY Mellon had $41.7 trillion in assets under custody and/or administration, and $2.2 trillion in assets under management. BNY Mellon can act as a single point of contact for clients looking to create, trade, hold, manage, service, distribute or restructure investments. BNY Mellon is the corporate brand of The Bank of New York Mellon Corporation (NYSE: BK). Additional information is available on www.bnymellon.com Follow us on Twitter @BNYMellon or visit our newsroom at www.bnymellon.com/newsroom for the latest company news.

Remote/virtual work is an option.

Team overview
With large and global operations, model risk underlies much of what we do.  The Model Risk Management Group (MRMG) oversees all of the bank’s modelling.  It sets standards for development and approves all models before they are used in the firm.  Through intense interrogation of methodologies and comparison with its own models, the team aims to root out how each model will fail and ensure controls are in place. MRMG operates as a global group; the team in Poland is an integral part with highly visible roles, including leadership positions.  Decisions are reported to Senior Management and the Board of Directors on a regular basis. The role provides constant quantitative challenges and growing opportunities due to the diversity of projects.

Your role
As a Model Risk Specialist you will be responsible for reviewing machine learning and artificial intelligence approaches.  This requires challenging the ML/AI models built by the model development team and designing and executing tests for conceptual framework and outcomes. The role may require building benchmarks (shadow frameworks) that run alongside those in production, allowing MRMG to monitor performance in real time. You will be guided by more senior colleagues that help establish the validation scope. The work is highly independent and requires responsibility and accountability for accuracy and quality.

Qualifications

• Master’s Degree/PhD in a quantitative discipline (engineering or mathematics or physics or  statistics or econometrics or data science)
• The candidate must have a superb quantitative and analytical background with a solid theoretical foundation,
• Understanding of design, development, and implementation of machine learning and artificial intelligence models
•  2-5 years of modeling experience
• Programming skills in one of those languages: Python, R, Matlab or similar,
• Good communication skills. The candidate should have a strong interest in:  financial engineering or products of financial markets or statistics or econometric modeling or data science or machine learning.

Our offer
•    Full time contract of employment
•    City Centre locations close to main railway station and flexible working arrangements
•    Flexible benefits package, including life and medical insurance, health screening, fitness discount programme, employee assistance program
•    Award-winning Wellbeing Program supporting you with your unique health and wellbeing needs
•    Pension scheme
•    On-site childcare and a parental buddy programme
•    Exciting opportunities for career and global mobility
•    Diverse and inclusive environment
•    Employee Referral Program
•    Recognition programmes

BNY Mellon is an Equal Employment Opportunity Employer.
Our ambition is to build the best global team – one that is representative and inclusive of the diverse talent, clients and communities we work with and serve – and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family-friendly, inclusive employment policies and employee forums.

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