Remote Junior Data Scientist: ML, Embeddings & AI Agents

Satalia; United States; Remote; USD 50,000 - 83,000; Full time

Benefits offered by this job

Healthcare benefits

Flexible hours

Job summary

Satalia is seeking a junior data scientist to contribute to applied data science and ML projects, collaborating with senior scientists, engineers, and domain experts to develop models and AI agents for production use. The role is full time and fully remote from Greece, offering opportunities to work on multimodal datasets and synthetic data within a collaborative team.

You will write clean, tested code, move between workstreams, and learn methods as the field evolves, with emphasis on embeddings

Qualifications

• Degree in computer science, statistics, mathematics, or another quantitative discipline.
• Up to two years of data science or machine learning experience, including internships or substantial academic work.
• Solid statistics and machine learning foundations for structured and unstructured data.
• Good Python skills and familiarity with common data science tools.

Responsibilities

• Explore multimodal datasets and create features and data pipelines for modeling work.
• Build and evaluate machine learning models and agents with guidance from experienced teammates.
• Write clean, tested, reviewed code that can be prepared for production deployment.
• Move between workstreams and learn methods as project needs and the field evolve.
• Contribute to work involving probabilistic modeling, geospatial analysis, federated learning, and synthetic data.

Skills

Python programming

Statistics foundations

Curiosity & communication

ML basics

Education

Degree in computer science or related quantitative field

Tools

Embeddings

Large language models

Job description

Satalia is seeking a junior data scientist to contribute to applied data science and ML projects, collaborating with senior scientists, engineers, and domain experts to develop models and AI agents for production use. The role is full time and fully remote from Greece, offering opportunities to work on multimodal datasets and synthetic data within a collaborative team.

You will write clean, tested code, move between workstreams, and learn methods as the field evolves, with emphasis on embeddings