Data Scientist – Production Engineering

Cordial

Data Scientist role at Cordial focusing on operationalizing and scaling data science models. Involves collaboration with teams to enhance model performance and reliability.

Posted 4/20/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $140,000 - $175,000 per yearWebsite

Tech Stack

Tools & technologies

AirflowAWSBigQueryCloudPython

About the role

Key responsibilities & impact

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

What you’ll need

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
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

Benefits

Comp & perks

Equity and bonus
Robust benefit plan (medical/dental/vision/life)
401k match
Flexible time off
Paid company holidays
Annual company conference
Childcare reimbursement
Continued education yearly reimbursements

ATS Keywords

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Hard Skills & Tools

data scienceproduction data scienceapplied MLPythondata pipelinesorchestration frameworksAWSdata warehouse solutionsbig data technologiesdistributed computing

Soft Skills

collaborationdebuggingproblem-solvingindependenceadaptabilityownershipautonomy