Data Scientist - Production Engineering

Cordial is a company founded on the belief of incorporating humanity and empathy into marketing. They are seeking a Data Scientist – Production Engineering to operationalize, optimize, and scale data science models and systems while collaborating closely with data scientists and engineering teams.

Responsibilities:

• Optimize existing data science models and systems for performance, scalability, and reliability
• Translate research-grade or prototype data science code into production-ready implementations
• Work with large datasets and improve efficiency related to memory usage, runtime, and compute cost
• Contribute to and maintain production data pipelines and workflows
• Collaborate closely with other data scientists to preserve model intent, correctness, and assumptions while improving implementation quality
• Debug and resolve issues in production or near-production data science workflows
• Improve robustness, monitoring, and maintainability of deployed models and pipelines
• Support iterative model improvements and system evolution as business needs change

Requirements:

• Bachelor's degree or higher in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field
• 3+ years of experience working with real-world, industry, or production data in a data science, applied ML, or analytics role
• Demonstrated experience contributing to production data science or analytics systems, not only exploratory or academic projects
• Strong programming skills in Python and experience writing maintainable, production-quality code
• Experience working with large datasets and performance-sensitive workflows
• Prior experience with data pipelines and orchestration frameworks (e.g., Dagster, Airflow, etc.)
• Cloud platform expertise, particularly AWS services (Glue, Athena, ECS, S3 Tables, etc.) for scalable data processing and model deployments
• Hands-on experience with modern data warehouse solutions (Snowflake, BigQuery, etc.) including query optimization, clustering strategies, and cost management
• Experience with big data technologies and distributed computing frameworks for handling enterprise-scale event datasets
• Solid understanding of data science fundamentals, including statistics and modeling concepts, sufficient to work closely with research-oriented data scientists
• Ability to work independently and ramp up quickly in an existing codebase and system
• Experience working in small, fast-moving teams where ownership and autonomy are expected