Data Scientist

About the Role

This full-time remote position offers flexible commitment ranging from 10 to 40 hours per week. The role involves designing and implementing data analysis challenges focusing on data cleaning, method comparison, and interpretation of results. You'll create clear, reproducible reference analyses using tools like Jupyter Notebook or Google Colab, ensuring fairness and thorough evaluation of analytical approaches through spot checks and objective recommendations. Collaboration with researchers and domain specialists is key to guarantee consistent, accurate assessment outcomes.

Responsibilities

• Develop realistic data-analysis challenges incorporating data preprocessing, comparison of analytical methods, and drawing conclusions from results.
• Prepare reproducible reference analyses using Jupyter or Colab notebooks.
• Construct tasks that enable fair benchmarking of different analytical techniques along with spot checks and expert recommendations.
• Assess the performance of models on designed tasks and validate the statistical integrity of conclusions.
• Work closely with researchers and specialists to maintain consistent and reliable evaluations.

Requirements

• Master's or PhD degree in statistics, data science, or a quantitative STEM discipline, or equivalent hands-on experience.
• Demonstrable experience in research, research engineering, or data analysis roles.
• Skilled in procedures such as data cleaning, statistical correlation analysis, hypothesis testing, and interpreting outcomes.
• Familiarity with Jupyter Notebooks or Google Colab for conducting analyses and documentation.
• Competent in Python programming, especially libraries like pandas and NumPy, along with practical knowledge of Git.
• Strong written communication skills to convey analytical findings effectively.
• Preferred experience includes AI training, model evaluation, or authoring benchmarks and tasks.