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As a Quantitative UX Researcher, you will be responsible for Survey Management, which includes design, implementation and deployment to collect generative and evaluative quantitative data, ensuring customer questions are clear, unbiased, and aligned with experience metrics, survey design format, scales, standards and research objectives.
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Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field. We use data, research, strategy, and empathy to guide multidisciplinary teams toward a common goal, balancing diverse perspectives and empowering our teams to do great work.
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2-3 years of relevant experience post Advanced degree (MS, PHD) in a quantitative field (e.g., Data Science, Computer Science, Applied Mathematics, Statistics, and Econometrics) You will work with the firm's rich data pool from both internal and external sources using Python/Spark via AWS and other systems.
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PhD in a quantitative field (e.g., Statistics, Applied Math, Engineering, Computer Science, Physics, Biology, Psychology, Political Science, etc.) You will work closely with product, engineering, and other data practitioners to translate business questions into quantitative artifacts.
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SP achieves this by using a combination of machine learning, big data analytics, ultra-low latency high-volume engineering systems, and quantitative product focus. Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
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Required Qualifications: Degree in Applied Math, Physics, Engineering, Quantitative Finance, Computer Science or other quantitative disciplinesUp to 4 years of experience in a relevant role such as software or quant developmentProficiency in at least one of Python, C.
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Bachelor's degree in a quantitative field like Data Science, Statistics, Applied Mathematics or Econometrics required. Support academic success for our students through the applied use of advanced analytics, and help to identify, pilot and test initiatives for prospects, students, and faculty that drive improved academic outcomes and achievements.
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Requirements: Requires a Master’s in Computer Science, Data Science, or a related field plus two (2) years of experience as an Applied Scientist, Data Scientist, or any occupation/position/job title involving experience in a highly quantitative field.
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2-4 years of experience working in a quantitative research capacity with a focus on Ags, Energy, Metals, Fixed Income, FX, or Equity Index strategies. Quantitative Researcher as part of a small, collaborative systematic global macro team with a focus on applying cutting edge techniques to strategies across the commodities, fixed income, and FX space.
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Bachelor's degree in Computer Science, Statistics, Data Science, Applied Mathematics, or related quantitative disciplines (Master's degree preferred). · Deep understanding of and experience with ML models and ML engineering, advanced statistics, time series forecasting, best practice application of data science in a business context (e.g., back-testing & piloting), model architecture, and use cases.
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A BA/BS degree in a quantitative discipline: computer science, statistics, applied mathematics, operations research, engineering, economics, etc. 2+ years of experience with Tableau, Looker or comparable data visualization tools.
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Preferred qualifications, capabilities, and skills 3+ years of experience working for a major financial institution as a software engineer, quantitative developer, or in a similar role. Job responsibilities Lead the systematic rebuild and optimization of a balance sheet optimizer application used to support senior management in formulating firm-wide strategies Architect and develop a comprehensive software solution that integrates advanced data engineering practices to streamline and enhance data processing, ensuring convenience to users, scalability, maintainability, and high performance.
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Bachelor's/Advanced degree in Financial Economics, Applied Mathematics, Physics, Statistics or other quantitative disciplines. Experience using Factset and/or other portfolio management and data toolkits.
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The ideal candidate will have a background in applied statistics, economics or a related quantitative field, will have strong business acumen, experience working with large data sets, and experience interacting with business partners.
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Common areas of study include but are not limited to:Economics Computer Science Data Science Engineering Financial, Stochastic, and other applied Math Operations Research Statistics & econometrics Other STEM majors.
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applied quantitative data jobs in New York, NY
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