We are seeking analytical and technically proficient Junior Data Scientists to contribute to an AI model evaluation project focused on statistics, machine learning, experimentation, and quantitative reasoning. You will evaluate AI-generated responses to data science problems, develop prompts and reference solutions, identify methodological errors, and provide structured feedback to improve advanced AI systems.
Key Responsibilities
Evaluate AI-generated responses to data science, statistics, machine learning, and quantitative reasoning problems.
Develop technically accurate prompts, datasets, analytical problems, and reference solutions for AI model training and evaluation.
Assess the correctness, reliability, and methodological soundness of statistical analyses and machine learning approaches.
Identify errors in calculations, statistical assumptions, experimental design, model selection, and quantitative reasoning.
Validate Python-based analytical workflows and review code and outputs for accuracy.
Document findings, explain technical issues, and provide clear, structured feedback.
Develop challenging evaluation scenarios and maintain accuracy, consistency, reproducibility, and technical rigor.
Follow project guidelines, evaluation rubrics, and quality standards while meeting deliverables.
Required Qualifications
At least one year of relevant professional experience in data science, machine learning, quantitative analysis, statistics, or a related field, including some experience within the past three years.
Strong proficiency in Python and practical experience with Pandas.
Sound understanding of statistics, probability, hypothesis testing, statistical inference, machine learning, and model evaluation.
Understanding of data modeling, experimentation, and analytical methodologies.
Strong analytical, problem-solving, critical-evaluation, and written communication skills.
Ability to work independently, follow detailed instructions, and deliver accurate work remotely.
Preferred Qualifications
Experience in applied data science, machine learning research, quantitative modeling, or statistical analysis.
Familiarity with NumPy, SciPy, scikit-learn, Jupyter Notebooks, or related Python libraries.
Experience designing experiments, conducting A/B tests, evaluating AI outputs, or developing benchmark datasets.
A bachelor's or master's degree in a quantitative discipline; advanced research qualifications are an advantage.
Work Arrangement and Compensation
Engagement: Independent contractor, subject to the applicable agreement.
Work mode: Remote, subject to project eligibility and client approval.
Compensation: USD 150–200 per hour, subject to contractual terms, qualifications, and project requirements. Total earnings depend on assigned work and approved billable hours.
Schedule: As defined by project requirements and final engagement terms.
Candidates should confirm their country of residence and eligibility during the application process. International applicants may be considered subject to client eligibility and contracting requirements. Shortlisted candidates may be required to complete a technical assessment. The end client and confidential project details will be disclosed to shortlisted candidates at the appropriate stage.
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