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Quantitative Finance Forecasting Analyst
Job summary
A predictive analytics firm in the United Kingdom is seeking a Quantitative Finance Forecasting Analyst to review predictive models and validate quantitative assumptions. Responsibilities include evaluating model outputs and identifying anomalies in data. Ideal candidates will have a background in quantitative finance or statistics. The role offers competitive hourly compensation ranging from $60 to $120, making it an attractive opportunity in the field.
Qualifications
- Strong background in quantitative finance, statistics, or data analysis.
- Ability to reason around model logic and assumptions.
- Familiarity with Python or R is a plus.
Responsibilities
- Assess quantitative model outputs and data inputs.
- Validate forecasting assumptions and key drivers.
- Summarize expected trends or performance scenarios.
- Identify anomalies or inconsistencies in structured data.
- Deliver findings in standardized evaluation formats.
Skills
Alignerr supplies AI labs with forecasting and modeling specialists who evaluate quantitative signals and structured financial data.
The Quantitative Finance Forecasting Analyst reviews predictive models, validates quantitative assumptions, and interprets outputs related to market or company-level forecasting.
- Assess quantitative model outputs and data inputs
- Validate forecasting assumptions and key drivers
- Summarize expected trends or performance scenarios
- Identify anomalies or inconsistencies in structured data
- Deliver findings in standardized evaluation formats
- Background in quantitative finance, statistics, or data analysis
- Strong reasoning around model logic and assumptions
- Familiarity with Python, R, or other modeling tools
$60 - $120 an hour
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.