Quantitative Finance Forecasting Analyst

Alignerr Corp.; Seattle (WA); Remote; USD 83,000 - 124,000; Part time

Job summary

Alignerr seeks a Quantitative Finance Forecasting Analyst (AI Training) to review AI-generated market forecasts, validate model inputs, and assess assumptions. This fully remote, hourly contract role suits finance and data professionals who rigorously test numbers and logic.

You will work asynchronously, interpret structured financial data, and deliver clear findings to support AI-driven finance reasoning. Flexible schedule and project-based workload.

Qualifications

• Strong background in quantitative finance, statistics, economics, or data analysis.
• Sharp reasoning when it comes to model logic, assumptions, and limitations.
• Comfortable working with structured financial datasets and interpreting complex outputs.
• Detail-oriented and systematic — you notice when numbers don't add up.
• Clear, concise written communicator who can translate technical findings into accessible summaries.
• Self-motivated and reliable when working independently without supervision.

Responsibilities

• Review and assess quantitative model outputs and their underlying data inputs
• Validate forecasting assumptions and identify the key drivers behind predictions
• Summarize expected trends and performance scenarios with clarity and precision
• Identify anomalies, inconsistencies, or logical gaps in structured financial data
• Deliver structured findings using standardized evaluation formats
• Work independently and asynchronously — on your own schedule

Skills

Quantitative finance

Statistics

Data analysis

Model validation

Written communication

Tools

Python

R

Job description

Quantitative Finance Forecasting Analyst (AI Training)

About The Role

What if your quantitative finance expertise could directly shape how AI understands markets, models risk, and interprets financial data for millions of users worldwide? We're looking for Quantitative Finance Forecasting Analysts to evaluate and validate AI-generated predictive models — ensuring the logic is sound, the assumptions hold up, and the outputs make sense in the real world.

This is a fully remote, flexible contract role built for finance and data professionals who think rigorously about numbers. If you can spot a flawed assumption, pressure-test a model, and communicate your findings clearly, this role was made for you.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: Flexible, task-based

What You'll Do

• Review and assess quantitative model outputs and their underlying data inputs
• Validate forecasting assumptions and identify the key drivers behind predictions
• Summarize expected trends and performance scenarios with clarity and precision
• Identify anomalies, inconsistencies, or logical gaps in structured financial data
• Deliver structured findings using standardized evaluation formats
• Work independently and asynchronously — on your own schedule

Who You Are

• Strong background in quantitative finance, statistics, economics, or data analysis
• Sharp reasoning when it comes to model logic, assumptions, and limitations
• Comfortable working with structured financial datasets and interpreting complex outputs
• Detail-oriented and systematic — you notice when numbers don't add up
• Clear, concise written communicator who can translate technical findings into accessible summaries
• Self-motivated and reliable when working independently without supervision

Nice to Have

• Hands-on experience with Python, R, or other quantitative modeling tools
• Background in financial forecasting, risk modeling, or investment analysis
• Familiarity with AI evaluation workflows or data annotation platforms
• Experience in roles such as quant analyst, actuary, data scientist, or financial modeler

Why Join Us

• Work on cutting-edge AI projects alongside leading research labs
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with the structure of meaningful, task-based work
• Apply deep domain expertise to problems that directly shape how AI reasons about finance
• Potential for ongoing work and contract extension as new projects launch