Applied Scientist

Remotebridge; United States; Remote; USD 80,000 - 140,000; Full time

Job summary

Remotebridge is seeking an Applied Scientist contractor to design and run statistical analyses and build ML models remotely.

You will collaborate with stakeholders, document methods, and ensure reproducible code; strong Python, Pandas, and scikit-learn skills required.

This role emphasizes clear communication, rigorous experimentation, and delivering actionable insights.

Qualifications

• Experience with Python data libraries such as Pandas and scikit-learn.
• Applied statistics, experimental design, and ML model evaluation.
• Ability to work on open or cross-functional data science projects.
• Excellent written and verbal communication; strong documentation.

Responsibilities

• Design and execute statistical analyses on complex datasets.
• Develop and validate ML models for business or research goals.
• Apply data modeling and large-scale data transformations in Python.
• Collaborate with stakeholders to define experimentation frameworks.
• Document methodology and findings with clarity.
• Deliver reproducible code and analytic reports.

Skills

Python

Pandas

scikit-learn

Machine learning

Applied statistics

Experimental design

Tools

NumPy

Job description

Role Title: Applied Scientist

Role Type: Contractor

Location: Remote

Scope of Work

• Design and execute statistical analyses to uncover actionable insights from complex datasets.
• Develop and validate machine learning models for various business or research objectives.
• Apply data modeling techniques and manage large-scale data transformations using Python and Pandas.
• Collaborate with stakeholders to define experimentation frameworks and analyze outcomes.
• Document methodology, findings, and recommendations with a focus on clarity and precision.
• Review peer contributions and provide high-quality feedback to support knowledge sharing.
• Deliver reproducible code and well-organized analytical reports as part of the project deliverables.
• Evaluate AI model outputs on statistics, machine learning, experimentation, and quantitative problems.
• Create expert-level prompts, datasets, and reference solutions.
• Identify flawed methodology, statistical errors, and weak quantitative reasoning.
• Provide clear, structured feedback that improves model capability.

Preferred Qualifications

• At least one year at a top company (tech, finance, or research).
• Expertise in Python, including proficiency with libraries such as Pandas and scikit-learn (sklearn).
• Demonstrated experience in applied statistics, experimental design, and machine learning.
• Proven ability to develop, tune, and evaluate machine learning models in practical settings.
• Strong data modeling skills and experience managing structured and unstructured data.
• Excellent written and verbal communication skills, with a passion for clear technical documentation.
• Experience collaborating on open or cross-functional data science projects is a plus.
• Advanced academic background or hands-on work in data science, applied mathematics, or related fields.