Machine Learning Operations Engineer - Database Marketing
Skills
About This Role
Overview
- The primary duties and responsibilities of this role are:
- Deploy, monitor, and maintain machine learning models used across gaming marketing and player analytics.
- Operationalize Data Science outputs by building automated pipelines for scoring, segmentation, and campaign ready datasets.
- Ensure high reliability and uptime for model workflows, including job scheduling, error detection, and alerting.
- Collaborate with Data Scientists to productionize new models, optimize runtime performance, and improve stability.
- Build and maintain data pipelines supporting model features, input refreshes, and scheduled scoring processes.
- Implement QA processes to identify data drift, model degradation, and operational anomalies.
- Maintain version control and documentation for models, pipelines, and deployment procedures.
- Partner with Campaign Operations to ensure model outputs align with business logic, targeting requirements, and production schedules.
- Work with IT and infrastructure teams on compute resources, storage, and system performance.
- Support model retraining cycles, testing, and controlled rollouts of updated logic.
- Ensure compliance with internal data governance and security standards.
About You
- Master s or PhD in Computer Science, Engineering, Data Science, Statistics or a related technical field required.
- 5+ years of experience in Data Science, ML Ops, data engineering, or production level machine learning environments.
- Strong experience with Python, SQL, and workflow orchestration tools (Airflow or similar).
- Experience working with cloud-based data platforms.
- Familiarity with machine learning model lifecycle management, CI/CD pipelines, and version control (Git).
- Able to translate analytical requirements into stable, production ready workflows.
- Comfortable working in fast paced environments with daily and weekly operational deliverables.
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