Python Developer (Data & Statistics) - (Freelance, Remote, 20+ openings)

Project Description

We are looking for a Mid-Level Python Developer to join our Al-driven statistical research

project. In this role, you'll build scripts that perform core statistical analysis on data

extracted from PDFs and web sources. You'll work with NumPy and vanilla Python (no

external ML libraries) to implement methods that bring datasets to life, ensuring results are

reproducible and reliable.

Compensation

Compensation is competitive and varies based on education level, institution, and prior experience.

Responsibilities:

• Write Python scripts using NumPy and vanilla Python to perform statistical analysis.• Implement custom statistical functions (e.g. chi-square tests, geometric mean,correlations).• Carry out linear regression without external ML libraries.• Perform data transformations (inflation adjustments, date mapping, digit extraction).• Document your reasoning and ensure results are clear, reproducible, and reliable.• Collaborate with data annotators to process and analyze extracted datasets. Experience

• 2-4 years of professional experience in Python development, data analysis, or

applied statistics.

• Proficiency with NumPy for array operations and statistical calculations.

• Strong ability to implement formulas directly from documentation.

• Solid understanding of probability, regression, and hypothesis testing.

• Excellent communication and documentation skills in English.

• Bachelor's degree in Computer Science, Statistics, Mathematics, Economics, or a

related field (preferred).

Application & Onboarding Process

Apply via partner site - Braintrust will send you an email with detailed instructions.Qualification exam (1–2 hours): evaluates your role-specific expertise. Compensation provided upon passing.Project exam (1–2 hours): evaluates your adherence to project guidelines and ability to produce math-specific deliverables. Compensation provided upon passing. Commitment

We expect a minimum of 17–20 hours per week, however considering the project scope and timelines the preferred and recommended commitment would be 8 hours/day. #LI-Remote