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Weekday (YC W21)Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates foundational knowledge in Data Science, Statistics, and Machine Learning, with strong analytical and problem-solving skills to evaluate AI-generated outputs and provide actionable feedback. Proficient in Technical Writing and Documentation to clearly communicate complex quantitative concepts.
Highest-signal resume keywords
Data Science FundamentalsStatistics and ProbabilityMachine Learning FundamentalsPython ProgrammingAnalytical Problem-Solving
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Evaluate AI-generated outputs on data science, statistics, machine learning, experimentation, and quantitative analysis tasks
- Create challenging, well-defined prompts and technical problems assessing analytical reasoning and practical data science skills
- Prepare and validate datasets for testing AI models across statistical and machine learning use cases
- Develop accurate reference answers, calculations, and analytical solutions for evaluation benchmarks
- Identify statistical errors, incorrect assumptions, flawed methodologies, and inappropriate data interpretations
- Assess mathematical reasoning, analytical methods, and evidence-based conclusions in AI-generated solutions
- Provide clear, actionable feedback on errors, missing steps, and improvement opportunities
- Validate analytical results, review solution consistency, and ensure objective, reproducible evaluation criteria
- Explain statistical concepts, analytical approaches, and evaluation findings through technical documentation
Requirements
What you’ll need- At least one year of professional experience at a well-established company in technology, finance, research, or a related field
- At least part of the relevant professional experience should have been gained within the past three years
- Foundational knowledge of data science, statistics, machine learning, and quantitative analysis
- Strong analytical and problem-solving skills, with the ability to evaluate data-driven conclusions critically
- Understanding of statistical methods, experimental design, data interpretation, and model evaluation
- Ability to identify incorrect calculations, methodological weaknesses, and unsupported conclusions
- Strong written communication skills, particularly when explaining technical and statistical concepts
- Ability to work independently, follow evaluation guidelines, and deliver accurate, high-quality assessments
- Data Science Fundamentals
- Statistics and Probability
- Machine Learning Fundamentals
- Quantitative Reasoning
- Data Analysis and Interpretation
- Statistical Methodology
- Analytical Problem-Solving
- Technical Writing and Documentation
- Python Programming
- SQL and Data Manipulation
- Pandas, NumPy, and scikit-learn
- Experimental Design and Hypothesis Testing
- Predictive Modeling and Model Evaluation
- Dataset Creation and Validation
- AI Model Evaluation and Benchmarking
- Experience in Technology, Finance, or Research Organizations
- Experience working at a recognized technology company, financial institution, or research organization
- Professional exposure to statistical analysis, machine learning projects, quantitative research, or data-driven decision-making
- Familiarity with evaluating AI-generated answers or validating analytical solutions
- Ability to communicate complex quantitative concepts in clear, concise English
- Candidates based in English-speaking countries are preferred.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Quantitative ReasoningData Analysis and InterpretationStatistical MethodologyExperimental Design and Hypothesis TestingPredictive Modeling and Model EvaluationDataset Creation and ValidationAI Model Evaluation and BenchmarkingSQL and Data ManipulationPandasNumPy
Soft Skills
Strong Written Communication SkillsAbility to Work Independently
Industry Keywords
Experience in TechnologyExperience in FinanceExperience in Research OrganizationsEvaluating AI-Generated AnswersData-Driven Decision-Making