Quantitative Finance Forecasting Analyst
- Toronto, Ontario, Canada
- Télétravail
- Publié 24 sept. 2026
- 1 poste
60 $ US–120 $ US / heure
Ouvre un site externe
- Type d’emploi
- Contrat
- Niveau d’expérience
- Débutant, Junior · 0+ ans
- Postuler avant le
- 18 oct. 2026
- Langue de l’offre
- anglais
- Heures de travail
- 40 heures par semaine
- Exigences de lieu
- Country, Toronto, Ontario, Canada
- Niveau d’expérience
- Entry level
Résumé du poste
The analyst will evaluate AI-generated predictive models and financial data to ensure accuracy, logical soundness, and consistency. They will also summarize market trends and identify anomalies within structured financial datasets.
Détails du poste
Quantitative Finance Forecasting Analyst (AI Training) About The Role What if your expertise in quantitative finance could directly shape how AI reasons about markets, models, and financial forecasts? We're looking for Quantitative Finance Forecasting Analysts to evaluate AI-generated predictive models and financial outputs — catching flawed assumptions, identifying data inconsistencies, and ensuring AI-driven forecasting is grounded in sound analytical logic. This is a fully remote, flexible contract role. No AI background required — just a strong command of quantitative finance, statistical reasoning, and model evaluation. Organization: Alignerr Type: Hourly Contract Location: Remote Commitment: Flexible, task-based What You'll Do Review and critically evaluate AI-generated predictive model outputs and quantitative data inputs Validate forecasting assumptions, key drivers, and underlying logic for accuracy and soundness Summarize expected market or company-level trends and performance scenarios in clear, structured formats Identify anomalies, inconsistencies, or errors within structured financial datasets Deliver findings using standardized evaluation frameworks and rubrics Work independently and asynchronously — fully on your own schedule Who You Are Solid background in quantitative finance, statistics, econometrics, or data analysis Sharp analytical thinker with strong reasoning around model logic, assumptions, and outputs Comfortable working with structured financial data and interpreting complex quantitative signals Detail-oriented and consistent — you notice when something doesn't add up Clear written communicator who can document findings concisely and precisely No prior AI experience required Nice to Have Familiarity with Python, R, MATLAB, or other quantitative modeling tools Experience in financial modeling, risk analysis, or investment research Background in economics, actuarial science, or applied mathematics Prior exposure to model validation, backtesting, or quantitative research workflows 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 your quantitative expertise to directly improve how AI reasons about financial data Potential for ongoing work and contract extension as new projects launch
Ce que vous ferez
The analyst will evaluate AI-generated predictive models and financial data to ensure accuracy, logical soundness, and consistency. They will also summarize market trends and identify anomalies within structured financial datasets.
Exigences
Candidates must possess a strong background in quantitative finance, statistics, or econometrics with sharp analytical reasoning skills. No prior AI experience is required, but proficiency in financial modeling and quantitative tools is highly valued.
Compétences indiquées
- Analyse de données · Souhaitée
- Python · Souhaitée
Autres compétences pertinentes
Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.
- Quantitative finance
- Statistical reasoning
- Model evaluation
- Data analysis
- Econometrics
- Financial modeling
- Risk analysis
- Investment research
- Python
- R
- MATLAB
- Actuarial science
- Applied mathematics
- Backtesting
- Model validation
Domaines d’emploi
- Finance & Accounting
- Data & Analytics
- Science & Research
- Technology
- Software
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