Remote Data Scientist & Quantitative Researcher

Synthires; Greater London; Remote; GBP 153,000 - 205,000; Full time

Benefits offered by this job

Fully remote work

Job summary

Synthires in the United Kingdom is seeking Data Scientists and Quantitative Professionals to support an AI research project. You’ll evaluate model performance across statistics, ML, experimentation, and quantitative reasoning to improve accuracy and analytical capabilities.

Key responsibilities include evaluating AI outputs, creating prompts and datasets, and identifying methodological flaws. Strong communication of technical concepts in writing is essential for collaboration with

Qualifications

• 1 year of experience at a leading company in technology, finance, research, or related field.
• Experience within the past 3 years.
• Strong understanding of Python, statistics, machine learning, and data analysis.
• Experience with Pandas, data modeling, and experimentation.
• Strong analytical and quantitative reasoning.
• Ability to communicate technical and statistical concepts clearly in writing.
• Based in an English-speaking country.

Responsibilities

• Evaluate AI-generated outputs involving data science, statistics, machine learning, and quantitative problems.
• Create challenging prompts, datasets, and reference solutions.
• Identify flawed methodologies, statistical errors, and weaknesses in quantitative reasoning.
• Assess data analysis, experimentation approaches, and data modeling techniques.

Skills

Python

Statistics

Machine Learning

Data analysis

Data modeling

Experimentation

Analytical reasoning

Written communication

English proficiency

Tools

Pandas

Job description

Synthires in the United Kingdom is seeking Data Scientists and Quantitative Professionals to support an AI research project. You’ll evaluate model performance across statistics, ML, experimentation, and quantitative reasoning to improve accuracy and analytical capabilities.

Key responsibilities include evaluating AI outputs, creating prompts and datasets, and identifying methodological flaws. Strong communication of technical concepts in writing is essential for collaboration with