Data Scientist - Machine Learning

This is a remote position.

What You'll Do

• Develop, deploy, and maintain production machine learning models.
  

• Perform exploratory data analysis and feature engineering to extract actionable insights.
  

• Build and improve data pipelines that support ML workflows and automation.
  

• Collaborate with engineering and business stakeholders to deliver scalable ML solutions.
  

• Contribute to AI/LLM-based capabilities where applicable to enhance product offerings.
  

• Monitor and optimize model performance in production environments (not only notebook-based development).
  

• Document all procedures, configurations, and changes in a clear, auditable manner.
  

What You'll Need

• 2+ years of experience building and maintaining production machine learning models.
  

• Strong Python programming skills.
  

• Experience with AWS SageMaker or another enterprise ML platform (e.g., Vertex AI or Azure ML) supporting production ML pipelines.
  

• Experience deploying and monitoring ML models in production (not only notebook-based development).
  

• Advanced SQL.
  

• Git/version control.
  

• Ability to work independently in production environments.
  

• Experience with MLOps tools (MLflow, Airflow, dbt, or similar).
  

• Snowflake.
  

• Marketing, growth, experimentation, or causal inference experience.
  

• Experience with LLMs or AI agents.
  

• Agile development practices.
  

• Experience building scalable ML solutions in enterprise environments.
  

• Familiarity with cloud-based ML platforms and production deployment best practices.
  

• Strong communication skills and ability to work with cross-functional teams.
  

• Familiarity with US time zones (PST to EST) and remote collaboration workflows.
  

• Be part of a remote-first organization where flexibility is embraced.
  

• Work and learn alongside talented engineers and technology leaders.
  

• Explore opportunities to learn and grow through technical and non-technical training programs.
  

• Gain global exposure by working on products with international teams and clients.
  

• Attend virtual and in-person international technology conferences to expand your knowledge and network.