Junior Data Scientist

This role is for one of our clients Pay: 150-200/hour Role Type: Contractor Location: Remote We are seeking a detail-oriented Junior Data Scientist to contribute to the evaluation and improvement of advanced artificial intelligence systems. This opportunity is ideal for early-career data science professionals with strong analytical skills and a solid understanding of statistics, machine learning, experimentation, and quantitative reasoning. In this role, you will evaluate AI-generated responses to data science and quantitative problems, develop expert-level prompts and datasets, and create reference solutions to assess the accuracy and reliability of AI models. You will identify statistical errors, flawed methodologies, and weaknesses in quantitative reasoning while providing structured feedback to improve model performance. The ideal candidate combines practical data science knowledge with clear technical communication and a rigorous, evidence-based approach to problem-solving. Previous experience in AI development is not necessarily required. Requirements Key Responsibilities AI Model Evaluation: Evaluate AI-generated outputs on data science, statistics, machine learning, experimentation, and quantitative analysis tasksProblem and Prompt Development: Create challenging, well-defined prompts and technical problems that assess analytical reasoning and practical data science skillsDataset Preparation: Prepare and validate relevant datasets for testing AI models across statistical and machine learning use casesReference Solution Development: Develop accurate reference answers, calculations, and analytical solutions to establish reliable evaluation benchmarksStatistical Validation: Identify statistical errors, incorrect assumptions, flawed methodologies, and inappropriate interpretations of dataQuantitative Reasoning Assessment: Assess whether AI-generated solutions demonstrate sound mathematical reasoning, appropriate analytical methods, and evidence-based conclusionsStructured Feedback: Provide clear, actionable feedback highlighting errors, missing steps, and opportunities to improve the accuracy and reliability of AI-generated outputsQuality Assurance: Validate analytical results, review solution consistency, and ensure that evaluation criteria are objective and reproducibleTechnical Documentation: Explain statistical concepts, analytical approaches, and evaluation findings in a clear and structured manner Required Qualifications At least one year of professional experience at a well-established company in technology, finance, research, or a related fieldAt least part of the relevant professional experience should have been gained within the past three yearsFoundational knowledge of data science, statistics, machine learning, and quantitative analysisStrong analytical and problem-solving skills, with the ability to evaluate data-driven conclusions criticallyUnderstanding of statistical methods, experimental design, data interpretation, and model evaluationAbility to identify incorrect calculations, methodological weaknesses, and unsupported conclusionsStrong written communication skills, particularly when explaining technical and statistical conceptsAbility to work independently, follow evaluation guidelines, and deliver accurate, high-quality assessments Must-Have Skills Data Science FundamentalsStatistics and ProbabilityMachine Learning FundamentalsQuantitative ReasoningData Analysis and InterpretationStatistical MethodologyAnalytical Problem-SolvingTechnical Writing and Documentation Good-to-Have Skills Python ProgrammingSQL and Data ManipulationPandas, NumPy, and scikit-learnExperimental Design and Hypothesis TestingPredictive Modeling and Model EvaluationDataset Creation and ValidationAI Model Evaluation and BenchmarkingExperience in Technology, Finance, or Research Organizations Preferred Qualifications Experience working at a recognized technology company, financial institution, or research organizationProfessional exposure to statistical analysis, machine learning projects, quantitative research, or data-driven decision-makingFamiliarity with evaluating AI-generated answers or validating analytical solutionsAbility to communicate complex quantitative concepts in clear, concise EnglishCandidates based in English-speaking countries are preferred