Paulina Herman

Key Skills

Software

Mercor

Top Subject Matter

Business Domain Expertise

Financial Compliance & Risk Analysis

Consulting Domain Expertise

Top Data Types

Text

Document

Top Task Types

Segmentation

Classification

Text Generation

Question Answering

Evaluation Rating

Prompt Response Writing SFT

Freelancer Overview

Project Manager and strategy consulting professional with 10+ years of experience delivering complex programmes across consulting, financial services, AI, and eCommerce. Former EY-Parthenon consultant with a strong track record in M&A, commercial due diligence, and large-scale transformation initiatives. Experienced in leading cross-functional projects from strategy through execution, managing stakeholders, timelines, budgets, and risks to deliver high-impact outcomes in fast-paced environments. Combines strong financial and analytical capabilities, including valuation, financial modelling, and market analysis, with hands-on delivery experience and a structured, problem-solving approach. Currently working in AI model evaluation, designing structured business scenarios, developing evaluation frameworks and rubrics, and assessing model reasoning to enhance decision-making in advanced AI systems.

Labeling Experience

Consulting/Finance Expert and AI Model Evaluator (Contractor, Mercor AI)

MercorText

Provided evaluation and rating of AI model performance within complex business and consulting scenarios. Developed structured evaluation frameworks and rubrics to assess reasoning, accuracy, and consistency in AI outputs. Simulated real-world commercial and financial decision-making contexts for advanced AI models. • Designed business case scenarios to test model reasoning and decision-making • Assessed and rated ambiguous and multi-step problem sets produced by AI models • Identified gaps and recommended improvements to model logic and reliability • Contributed to enhanced decision-making capabilities in AI systems

Provided evaluation and rating of AI model performance within complex business and consulting scenarios. Developed structured evaluation frameworks and rubrics to assess reasoning, accuracy, and consistency in AI outputs. Simulated real-world commercial and financial decision-making contexts for advanced AI models. • Designed business case scenarios to test model reasoning and decision-making • Assessed and rated ambiguous and multi-step problem sets produced by AI models • Identified gaps and recommended improvements to model logic and reliability • Contributed to enhanced decision-making capabilities in AI systems

2025 - Present

Education

Work History