Reconciliation analyst Jobs in Brooks, AB
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Reconciliation analyst • brooks ab
Last updated: 4 days ago
In this hourly, remote contractor role, you will review AI-generated finance analyses and / or generate expert finance content, evaluating reasoning quality and step-by-step problem-solving while pro...Show moreLast updated: 30+ days ago
Are you ready to embark on an electrifying journey that will revolutionize the global food system?.Seize this opportunity to join the trailblazing team at TELUS Agriculture and Consumer Goods (TAC)...Show moreLast updated: 4 days ago
From the open road to the boardroom, we offer diverse career opportunities from coast-to-coast.We are seeking an experienced and highly analytical professional to join our team as a Senior NGL Anal...Show moreLast updated: 30+ days ago
Remote Senior Finance Specialist - AI Trainer
SuperAnnotateBrooks, Alberta, CARemote
Full-time
Consultant Assistant (Cattle Health)
TELUS Agriculture & Consumer GoodsBrooks, Alberta, CanadaPart-time
Senior Analyst
Superior PropaneAlberta, CanadaFull-time
- Edmonton, AB (from $ 130,546 to $ 131,261 year)
- Toronto, ON (from $ 58,500 to $ 127,665 year)
- Montreal, QC (from $ 50,625 to $ 115,115 year)
- Mississauga, ON (from $ 52,500 to $ 107,250 year)
- North York, ON (from $ 52,650 to $ 99,625 year)
- Calgary, AB (from $ 55,000 to $ 92,389 year)
- Richmond Hill, ON (from $ 52,650 to $ 72,316 year)
- Ottawa, ON (from $ 54,620 to $ 65,696 year)
Remote Senior Finance Specialist - AI Trainer
SuperAnnotateBrooks, Alberta, CA30+ days ago
Job type
- Full-time
- Remote
Job descriptionBachelor’s degree (or higher) in Finance, Economics, Accounting, Business, Financial Engineering, or Quantitative Finance (including coursework in Micro / Macro, Corporate Finance, Investments, Econometrics, and Accounting). 5+ years of professional experience in Finance, Economics, Accounting, Business, Financial Engineering, or Quantitative Finance. Strong command of financial statements, valuation (DCF and multiples), time value of money, and markets / instruments. Confident in risk / return reasoning, basic macro & microeconomic intuition, and financial modeling logic (assumptions, drivers, sensitivities, consistency checks). Able to rigorously review and explain reasoning, identify methodological errors, and fact-check claims with high attention to detail; Minimum C1 English proficiency. Comfortable applying structured sanity checks (conservation-style checks for finance : reconciliation, sign / units consistency, boundary cases, and plausibility bounds). Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones. Previous experience with AI data training / annotation, expert review, or editorial QA is strongly preferred.
In this hourly, remote contractor role, you will review AI-generated finance analyses and / or generate expert finance content, evaluating reasoning quality and step-by-step problem-solving while providing precise written feedback. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify methodological or conceptual errors; fact-check financial claims and assumptions; write high-quality explanations and model solutions; and rate and compare multiple responses based on correctness and reasoning quality. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your finance expertise directly helps improve the world’s premier AI models by making their financial reasoning more accurate, reliable, and clearly explained.
Key Responsibilities :
- Develop AI Training Content : Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
- Optimize AI Performance : Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
- Ensure Model Integrity : Test AI models for potential inaccuracies or biases, validating their reliability across use cases.
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