Data Scientist

Role Overview

Join Cordial’s data science team as a Data Scientist – Production Engineering. You will help operationalize, optimize, and scale data science models and systems that are already in production or are moving into production.

Key Missions

• Optimize existing data science models and systems for performance, scalability, and reliability.
• Productionize research/prototype code into production-ready implementations.
• Collaborate with other data scientists to preserve model intent, correctness, and assumptions while improving implementation quality.

Responsibilities

• Improve the implementation and performance of the data science stack.
• Work closely with data scientists, engineering, and product teams.
• Contribute to production data science and analytics systems (not only exploratory work).

Requirements

• Ability to ramp up quickly, work independently, and contribute with minimal onboarding.
• 3+ years working with real-world production/industry data in data science, applied ML, or analytics.
• Hands-on experience with modern data warehouse solutions (e.g., Snowflake, BigQuery), including:
  • query optimization
  • clustering strategies
  • cost management
• Experience with data pipelines and orchestration frameworks (e.g., Dagster, Airflow).
• Experience with large datasets and performance-sensitive workflows.
• Proven experience contributing to production data science/analytics systems.
• Experience with big data/distributed computing for enterprise-scale event datasets.
• Strong Python skills and ability to write maintainable, production-quality code.
• Solid understanding of data science fundamentals (statistics and modeling).
• Cloud expertise, especially AWS (e.g., Glue, Athena, ECS, S3 Tables) for scalable data processing and deployments.

Education

• Bachelor’s degree or higher in a quantitative field such as Data Science, Computer Science, Statistics, or Mathematics (or related).