Extensive experience in quantitative modeling using interactive computational platforms such as Python, R, MATLAB, or similar, using modern data structures, analysis, and visualization tools in production Windows and/or Linux environments is required.

Quantitative analysts at the Bank are expected to participate in supervisory work at large banking organizations, contribute to Federal Reserve System projects related to variety of quantitative topics such as stress test modeling, analyzing financial institution portfolios, and model risk management.

Plus 2 years of statistics or market research experience reflecting increasing levels of responsibility OR Master of Science Degree in a quantitative discipline which includes advanced data analysis (e.g. statistics, applied mathematics, physics, quantitative psychology, predictive analytics, chemistry, engineering, finance/economics, data science, computer science, etc.

BS degree in business/finance or a quantitative field such as quantitative finance, statistics, applied mathematics, engineering, or computer science. Post-graduate/Master's in business/finance or a quantitative field such as quantitative finance, statistics, applied mathematics, engineering, or computer science.

Our SVP, Model Risk Management is a member of a quantitative team that is providing second line of defence for HSBC’s model risk. Degree in a quantitative discipline like Financial Mathematics, Statistics, Econometrics, Quantitative Finance, Engineering or Physics.

In addition to initiating interactions with portfolio managers and portfolio specialists, the Senior Risk Manager will also be responsible for responding to ad-hoc requests for customized risk analysis which will require strong quantitative, analytical, and technical skills.

You will have the opportunity to work with cutting-edge technology and collaborate with top academic minds in the field of quantitative trading. Stay up-to-date with the latest advancements in quantitative trading and apply them to improve trading strategies.

Graduate degree in a related field (Computational Finance, Quantitative Finance, Engineering, Mathematics and Computer Science). The Quantitative Portfolio Analyst will be responsible for the implementation of quantitative portfolio management for retirement managed accounts and non-discretionary model portfolios.

We employ investment expertise, quantitative techniques, and technology to scale our investment process across a variety of multi-asset class strategies, investing in mutual funds, commingled pools, and ETFs. The PositionThe Quantitative Portfolio Analyst will be responsible for the implementation of quantitative portfolio management for retirement managed accounts and non-discretionary model portfolios.

These tests include qualitative and quantitative analysis of urine to determine compliance with prescription medications and/or use of illicit substances utilizing screening analyzer and LCMS. This position requires multitasking and superior accuracy, attention to details, efficiency and productivity.

The Johns Hopkins University Transplant Research Center (TRC) is seeking a Principal Biostatistician to lead their Epidemiology and Quantitative Analysis Core. The TRC integrates four research cores: Clinical Trials and Studies, Epidemiology and Quantitative Analysis, Ethics and Qualitative Studies, and Translational/ Basic Science.

This role will be part of our Quantitative Engineering team, which is responsible for architecting, developing, and maintaining systems that support quantitative trading. Deep domain experience with financial datasets including FactSet, Bloomberg, IBES, CompStat, S&P Global, Worldscope, Morningstar, MSCI, Reuters, IDC, Markit, BARRA, Axioma, Northfield, and PORT.

We assist companies and non-profit organizations in delivering benefits to their employees. Asset Management Technology (AMT) provides worldwide technology and support to all the Investment Management, Research, Trading, and Investment Operations functions.

The Asset Management Quant Research Engineering team is looking for a Vice President of Data Engineering who wishes to take on the challenge of building a world-class data operation. Deliver datasets from onboarding through mapping and automated DQ so they can be handed off to the Data Operations team for DQ maintenance and consumed by research teams and production.

Quantitative Developer as part of a small, collaborative systematic global macro team based in New York with a focus on applying cutting edge statistical and machine learning techniques to short-term strategies in futures, swaps, and FX markets.