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Applied Scientist - Machine Learning & Data Science

TekPillar
6 - 20 Years
Remote

Posted on: 22/10/2026

Job Description

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.

The job is for:

May work from home
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