Cordial Experience Inc. - Data Scientist - Production Engineering
Upload My Resume
Drop here or click to browse · Tap to choose · PDF, DOCX, DOC, RTF, TXT
Requirements
• Bachelor’s degree or higher in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field, plus 3+ years of experience working with real-world, industry, or production data in a data science, applied ML, or analytics role • , plus 3+ years of experience working with real-world, industry, or production data • Demonstrated experience contributing to production data science or analytics systems, not only exploratory or academic projects • production data science or analytics systems • Strong programming skills in Python and experience writing maintainable, production-quality code • Experience working with large datasets and performance-sensitive workflows • large datasets • The code word is #becordial • Prior experience with data pipelines and orchestration frameworks (e.g., Dagster, Airflow, etc.) • data pipelines and orchestration frameworks • 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 • data warehouse solutions • query optimization • Experience with big data technologies and distributed computing frameworks for handling enterprise-scale event datasets • big data technologies • 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 • small, fast-moving teams
Responsibilities
• Optimize existing data science models and systems for performance, scalability, and reliability • performance, scalability, and reliability • Translate research-grade or prototype data science code into production-ready implementations • 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. • production data pipelines and workflows. • Collaborate closely with other data scientists to preserve model intent, correctness, and assumptions while improving implementation quality • model intent, correctness, and assumptions • 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
Benefits
• APPLICATION INSTRUCTIONS • Resume Submission Requirement — Please Read Carefully • When uploading your resume, your file must be named in the following format: • FIRSTNAME-LASTNAME-CORDIAL2026 • Example: JOE-DOE-CORDIAL2026 • Applications that do not follow this naming convention exactly will be automatically rejected and will not be reviewed. Please double-check your file name before submitting. • Accepted file formats: PDF or Word (.docx) • WORK AUTHORIZATION • As of January 1, 2026, Cordial does not provide visa sponsorship, visa transfers, immigration support, or employment-related documentation for immigration purposes, including letters supporting visa applications, renewals, transfers, or work authorization, for new hires.
No credit card. Takes 10 seconds.