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EY Quantitative Analyst - FSRM QAS Trading United States, New York, New York 954131436
Ernst & Young U.S. LLP, New York, NY.
Advise clients on Financial Services issues in the financial services industry, focusing on quantitative analysis. Deliver services in market risk, counterparty credit risk, risk management and governance, model development and implementation, model/system documentation, and model benchmarking while establishing relationships with client personnel at appropriate levels. Design and apply quantitative techniques to help institutions develop and validate market risk modeling methodologies. Perform the practical application of advanced analytics techniques to help clients solve business problems and complex issues in the financial services industry. Apply statistical, economic, financial, or mathematical theories to process input data into quantitative estimates, which are used for identifying and measuring risks, valuing exposures, instruments or positions, conducting stress testing, assessing adequacy of capital, measuring compliance with internal limits, or meeting financial or regulatory reporting requirements. Demonstrate technical capabilities and professional knowledge. Communicate and interpret technical concepts to both technical and non-technical client stakeholders. Consistently deliver quality client services by leading teams, monitoring progress, managing risks and ensuring key stakeholders are kept informed about progress and expected outcomes.
Full time employment, Monday– Friday,40-45hours per week, 8:30 am – 5:30 pm.
MINIMUM REQUIREMENTS:
Must have Bachelor’s degree in Mathematics, Statistics, Economics, Computer Science, Engineering, Physics, Finance, Data Science or a related field and 5 years of progressive post-baccalaureate work experience in quantitative analysis.
Alternatively must have a Master’s degree in Mathematics, Statistics, Economics, Computer Science, Engineering, Physics, Finance, Data Science or a related field and at least 4 years of work experience in quantitative analysis.
Alternatively must have a PhD in Mathematics, Statistics, Economics, Computer Science, Engineering, Physics, Finance, Data Science or a related field and 2 years of work experience in quantitative analysis.
Must have 2 years of work experience in at least 3 of the following areas:
- Financial product engineering or research and development
- Designing and developing quantitative methods and services for capital markets and derivative products
- Front Office (FO) pricing models, Market and Counterparty Credit Risk models, liquidity models, treasury function models, operational risk models or Comprehensive Capital Analysis and Review (CCAR) models
- Statistical and numerical techniques and the principles of the theory of probability and stochastic calculus
- Functional knowledge related to some of the following: modeling knowledge of financial risks and derivative products (e.g., equity, FX, commodities, credit and interest rates), risk management, model development, model validation, advanced analytics (e.g., machine learning techniques)
- Functional experience in market risk modeling and associated methodologies and their role in the overall risk management framework.
- Advanced analytics models, building machine learning algorithms (using Random Forest, SVM, Deep Learning and similar techniques) or Blockchain development and application
- Big data, machine learning and AI techniques using one or combination of the following tools:
-
- Theano
- Torch
- Keras.
Must have at least 2 years of work experience in at least 2 of the following programming languages:
- R
- MATLAB
- C/C++
- Python
- Java
Requires domestic and regional travel up to 70% to serve client needs.
Employer will accept any suitable combination of education, training, or experience.
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. In addition, our Total Rewards package includes medical and dental coverage, pension and 401(k) plans, and a wide range of paid time off options. Join us in our team-led and leader-enabled hybrid model. Our expectation is for most people in external, client serving roles to work together in person 40-60% of the time over the course of an engagement, project or year. Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances. You’ll also be granted time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
- Continuous learning: You’ll develop the mindset and skills to navigate whatever comes next.
- Success as defined by you: We’ll provide the tools and flexibility, so you can make a meaningful impact, your way.
- Transformative leadership: We’ll give you the insights, coaching and confidence to be the leader the world needs.
- Diverse and inclusive culture: You’ll be embraced for who you are and empowered to use your voice to help others find theirs.
EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.
For those living in California, please
EY is committed to providing reasonable accommodation to qualified individuals with disabilities, including veterans with disabilities. If you have a disability and either need assistance applying online or need to request an accommodation during any part of the application process, please call 1-800-EY-HELP3, type Option 2 (HR-related inquiries) and then type Option 1 (HR Shared Services Center), which will route you to EY’s Talent Shared Services Team or email SSC Customer Support at ssc.customersupport@ey.com.
This particular position at Ernst & Young in the United States requires the qualified candidate to be a "United States worker" as defined by the U.S. Department of Labor regulations at 20 CFR 656.3. You can review this definition at https://www.gpo.gov/fdsys/pkg/CFR-2011-title20-vol3/pdf/CFR-2011-title20-vol3-sec656-3.pdf at the bottom of page 750. Please feel free to apply to other positions that do not require you to be a "U.S. worker".
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