Senior Data Scientist - Remote AI Model Evaluation

Synthires; California; Remoto; USD 207.000 - 276.000; Tempo pieno

Vantaggi offerti da questo lavoro

Fully remote work

Descrizione del lavoro

Synthires is seeking Data Scientists and Quantitative Professionals for a fully remote AI research project. You will evaluate AI model performance across statistics, ML, experimentation, and quantitative reasoning to improve model accuracy and analytical capabilities.

You will create prompts, datasets, and reference solutions; identify flawed methodologies and weaknesses in quantitative reasoning; and assess data analysis, experimentation approaches, and data modeling techniques.

Competenze

• At least 1 year of experience at a leading company in technology, finance, research, or a related field, with some 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 skills.
• Ability to communicate technical and statistical concepts clearly in writing.
• Based in an English-speaking country.

Mansioni

• 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.

Conoscenze

Python

Statistics

Machine learning

Data analysis

Quantitative reasoning

Strumenti

Pandas

Experimentation

Descrizione del lavoro

Synthires is seeking Data Scientists and Quantitative Professionals for a fully remote AI research project. You will evaluate AI model performance across statistics, ML, experimentation, and quantitative reasoning to improve model accuracy and analytical capabilities.

You will create prompts, datasets, and reference solutions; identify flawed methodologies and weaknesses in quantitative reasoning; and assess data analysis, experimentation approaches, and data modeling techniques.