ExxonMobil is looking to automate the deployment and sustainment of Data Science work products at scale to deliver value to customers in a reproducible way.
Requirements
- Applies Software Development methodologies
- DevOps toolsets
- ML techniques
- Infrastructure as Code
- Continuous Integration & Continuous Deployment principles
- ML Pipelines
- APIs
Responsibilities
- Applies Software Development methodologies, DevOps toolsets and ML techniques and coordinates the implementation effort of an end-to-end machine learning workflow that effectively brings ML models to production.
- Leads the scoping and identifies the appropriate solution design of a deployment of a new data science solution.
- Provisioning deployment environments via Infrastructure as Code
- Applying Continuous Integration & Continuous Deployment principles
- Developing relevant source code, ML Pipelines, APIs, and user interfaces
- Employing multiple testing methods to transform and scale a prototype data science model to a multi-user environment across business lines.
- Sustains solutions by enabling continuous ML model and/or service performance monitoring, training, and re-training of models, including the implementation of proactive alerting methods.
Other
- Mentors early career professionals
- Utilizes depth and/or breadth of experience to identify cross-functional business opportunities
- Visible mentor beyond immediate business line or team.
- Coaches users to improve ability to derive value out of processes, systems, and data.
- Application of business acumen functional skill applied to C&DS JF.
