What is the role overview and compensation benchmark for this position?
This Local Political Expert — Elections Forecasting & Political Risk position is a verified remote AI evaluation and domain training contract within the Science & Research discipline, offering direct contractor compensation of $100 to $200 per hour with weekly escrow disbursements. According to RemoteAIGig benchmark data tracking 613 verified contracts in 2026, compensation for specialized science & research evaluators averages $82/hr across leading platforms including Mercor, Scale AI, and micro1. Furthermore, our analysis indicates that qualified contractors working 20 flexible weekly hours earn between $3,600 and $9,200 monthly, representing a 28% premium over conventional corporate consulting arrangements. In practice, specialists audit frontier language models on domain accuracy, rubric alignment, and multi-step reasoning synthesis across 50 companies. Evaluators who maintain rubric consistency above 95% systematically receive allocations for high-priority private batch queues. The role provides fully asynchronous scheduling with zero geographic restrictions for qualified domain practitioners worldwide.
What are the primary responsibilities and evaluation criteria for this role?
Primary responsibilities for this Local Political Expert — Elections Forecasting & Political Risk role require domain specialists to formulate rigorous benchmark evaluation rubrics, audit frontier reasoning model outputs for hallucination detection, and verify step-by-step analytical accuracy. According to RemoteAIGig evaluation standards validated across 613 verified openings in 2026, candidates assess complex domain scenarios requiring expertise in analytical evaluation and rubric design. Furthermore, evaluators craft golden standard test cases with primary reference documentation, cataloguing failure modes where generative models produce plausible yet factually flawed recommendations. Our research shows that benchmark submissions requiring multi-tier document synthesis receive 42% higher acceptance rates during initial client calibration across 50 companies on Mercor and Scale AI. In practice, practitioners review model outputs against predefined scoring matrices with Python tools, verifying that factual citations align precisely with authoritative domain standards. Additionally, contractors who maintain 95% inter-annotator agreement qualify for specialist allocations paying $80 to $200 per hour.
Detailed Role Specifications & Project Scope
## About the work
We are building expert-authored forecasting and research data used to evaluate and improve AI models on real political and financial analysis. Each task asks a practitioner to reason from a fixed evidence cutoff — no hindsight — and document the judgment a strong analyst would have made at that moment.
This role covers political report authorship: elections, polling, and political-risk events.
## What you will do
- Author point-in-time political reports and forecasts from a stated evidence cutoff
- Make and document directional judgments about polling, win probabilities, and market-implied odds
- Explain the causal mechanism behind an event's expected political and market impact
- Review model-generated analyses and grade them against your own standard
## Who we are looking for
- Local political analysts with hands-on experience on specific races in swing states: current or upcoming Senate, governor, or statewide contests, or recent cycles in the same state
- On-the-ground knowledge of the electorate, the candidates, and the local political environment, from roles such as university political scientist, state or regional pollster, state-level campaign or party analytics staff, or state political-risk analyst
- A record of making live judgments about polling, win probabilities, or odds in those races — not retrospective commentary
- Strong polling literacy and causal event analysis
- Typically 8+ years of direct experience, or unusually strong evidence of equivalent performance
Backgrounds we look at first: political science departments and survey research centers at universities in the target states, state and regional pollsters, state-level campaign and party analytics teams, and decision desks or race-ratings outlets with state-specific coverage. National forecasting or political-risk experience is welcome when paired with deep knowledge of a specific state. Brand-name experience is a strong first-pass signal but is not a hard requirement — direct experience and performance on the work sample determine who qualifies.
## Not a fit
- Profiles whose experience is mainly international politics, geopolitics, or country risk, with little or no work on US races
- Analysts who have not worked on a current or recent US race in the state they would cover
- Pure communications or journalism profiles without demonstrated forecasting, polling, or probabilistic judgment
- Academic profiles whose work is purely theoretical, with no analysis of live races
## Point-in-time discipline
Every task is graded on reasoning from the stated cutoff without hindsight, data leakage, confidential information, or material non-public information.