Remote AI-Focused Quant Finance Forecasting Analyst

Alignerr Corp.; Hong Kong; Remote; HKD 541,000 - 811,000; Full time

Job summary

Alignerr is seeking a Quantitative Finance Forecasting Analyst (AI Training) to evaluate AI-generated model outputs, validate forecasting logic, and ensure financial predictions hold up across structured data. This fully remote hourly contract role fits finance and data professionals who think rigorously and communicate clearly.

You'll review model outputs, validate drivers, and summarize trends across scenarios, identifying anomalies in structured financial data.

Qualifications

• Strong background in quantitative finance, statistics, econometrics, or data analysis.
• Ability to reason through model logic, assumptions and downstream implications.
• Detail-oriented and systematic in evaluating forecasting outputs.
• Clear written communicator translating quantitative findings into structured outputs.

Responsibilities

• Review and assess quantitative model outputs, evaluating the soundness of inputs, assumptions, and results.
• Validate key forecasting drivers and identify where logic breaks down or assumptions are poorly grounded.
• Summarize expected market or company-level trends across a range of performance scenarios.
• Identify anomalies, inconsistencies, or red flags in structured financial data.
• Deliver clear, structured findings using standardized evaluation formats.
• Work independently and asynchronously — fully on your own schedule.

Skills

Quantitative finance

Statistics

Econometrics

Data analysis

Model reasoning

Technical communication

Independent work

Tools

Python

R

Job description

Alignerr is seeking a Quantitative Finance Forecasting Analyst (AI Training) to evaluate AI-generated model outputs, validate forecasting logic, and ensure financial predictions hold up across structured data. This fully remote hourly contract role fits finance and data professionals who think rigorously and communicate clearly.

You'll review model outputs, validate drivers, and summarize trends across scenarios, identifying anomalies in structured financial data.