Quantitative Analyst - QIS

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Salary

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Market context

U.S. role benchmark (BLS OEWS)

$106,409 U.S. median for this role

Projected growth (BLS Employment Projections)

+7.7% - Faster than average

Matched to SOC 13-2011 - Finance aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Finance From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Quantitative Analyst - QIS Required • Proficient in Python for developing quantitative analytics, models, and applications • Proficiency in at least one of statistical modelling, optimisation, or AI/ML techniques, with a solid understanding of the underlying mathematical theory • Experience working with large scale data analytics pipelines, with at least one of MS Azure Databricks, SQL, or KDB/Q • Strong analytical and problem solving skills, with the ability to work effectively in a front office environment • Academic background in Mathematics, Physics, Engineering, Computer Science, or a related STEM subject Preferred • Professional / internship experience in QIS, systematic trading, quantitative research, structuring, or front office quant roles within Global Markets • Knowledge of time series data analysis and experience with KDB/Q • Proficiency in additional programming languages such as C++ or Java; front end development experience (e.g. React/Enaml) is a plus • Experience with cloud based workflows and components, including Azure; exposure to platform or calculation stack transformation initiatives is advantageous • Strong knowledge of AI/ML techniques, with experience delivering such models into production environments a plus • Post graduate academic studies in a quantitative STEM subject

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