Data Science & Quantitative AI Evaluation Specialist
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Key details
- Location
- New Zealand
- Work style
- Remote
- Level
- Entry level
- Job type
- Contract
- Experience
- 1–4 yrs
- Function
- Data & ML
- Focus area
- AI / ML
- Posted
- 4d ago
Skills
About the role
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Role
We are looking for Data Scientists and Quantitative Professionals to help evaluate and improve next-generation AI models. You will assess AI-generated solutions to problems involving statistics, machine learning, experimentation, and quantitative reasoning. You will also create challenging prompts, datasets, and verified reference solutions while identifying methodological flaws, statistical errors, and weaknesses in analytical reasoning. This role is ideal for candidates with relevant professional experience in technology, finance, or research who can communicate technical concepts clearly.
SENIORITY: Junior / Early-Career Professional
LANGUAGE: Strong written English
LOCATION: Remote — English-speaking countries
Key Responsibilities
Evaluate AI-generated outputs across data science, statistics, machine learning, experimentation, and quantitative problem-solving.
Create expert-level prompts, datasets, and reference solutions for AI training and evaluation.
Identify flawed methodologies, statistical inaccuracies, unsupported assumptions, and weaknesses in quantitative reasoning.
Assess the correctness, reliability, and clarity of analytical approaches and conclusions.
Provide structured, evidence-based feedback to help improve AI model capabilities.
Apply consistent evaluation criteria and communicate technical findings clearly.
Requirements
At least one year of professional experience at a recognized company in technology, finance, or research, with some of that experience gained within the past three years.
Foundational knowledge of data science, statistics, machine learning, or quantitative analysis.
Strong analytical and critical-thinking skills, with the ability to identify errors in data-driven reasoning.
Excellent written English and the ability to explain technical and statistical concepts clearly.
Ability to evaluate complex problems systematically and provide accurate, well-supported feedback.
Current residence in an English-speaking country.
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