Applied Scientist - Machine Learning & Data Science
First seen by Alion on Oct 22, 2026.
About the Role:
We are looking for experienced Applied Scientists with strong expertise in Python, machine learning, statistics, and experimentation to contribute to an AI training project.
Key Responsibilities:
- Design and execute statistical analyses to extract meaningful insights from complex datasets.
- Develop, validate, tune, and evaluate machine learning models for business and research applications.
- Use Python, Pandas, and relevant data science libraries to analyze, transform, and model data.
- Design experiments, define evaluation metrics, and interpret experimental results.
- Evaluate AI-generated outputs involving statistics, machine learning, experimentation, and quantitative reasoning.
- Create challenging technical problems, expert-level prompts, datasets, and reference solutions.
- Identify statistical errors, flawed methodologies, and weaknesses in AI-generated reasoning.
- Document analytical approaches, findings, and recommendations through clear, reproducible code and technical reports.
- Review peer contributions and provide structured feedback to improve solution quality and model performance.
Tech Stack & Skills:
- Python Programming, Pandas, scikit-learn
- Machine Learning, Applied Statistics, Data Modeling
- Experimental Design, Model Evaluation and Validation
- Quantitative Reasoning, Technical Documentation
Required Qualifications:
- Strong hands-on experience in applied data science, machine learning, statistics, or a related quantitative field.
- Practical experience developing, tuning, and evaluating machine learning models.
- Strong understanding of statistical methods, experimental design, hypothesis testing, and data interpretation.
- Experience working with structured and/or unstructured datasets.
- Ability to identify methodological errors and assess the accuracy of quantitative solutions.
- Excellent written and verbal communication skills, with the ability to explain complex technical concepts clearly.
- A degree or advanced academic background in Data Science, Statistics, Applied Mathematics, Computer Science, or a related field is preferred.
- Experience at a leading technology company, financial institution, or research organization is an advantage.
Skills
Data Science, Machine Learning, Python, Pandas, Data Analytics