Reporting to the Director of Data Science Development, this Data Scientist IV specializing in AI Ops is an individual contributor role in the Data & AI Department on the Data Science Development team. This role is for a data scientist who is not only a strong critical thinker and problem solver but also a data science cloud architect and MLOps tools expert. They have a high proficiency in machine learning engineering as well as general data science and AI solution component engineering (beyond only ML), pipeline creation, and systems tooling used for deploying and maintaining end-to-end production data science or AI solutions in public Cloud platforms.
Sponsorship, in any form, is not available for this position.
Location: Remote, US
Role qualifications:
- Bachelor’s degree in (CS, Math, Data Science, Engineering, or other quantitative field) PLUS 7 yrs relevant work experience, or computational MS + 5 yrs, or PhD +3 yrs with computational research experience, or overall equivalent length of requisite work experience in lieu of a degree.
- Hands-on AI/ML algorithm development experience leveraging ML libraries and frameworks.
- Strong proficiency and real-world experience with developing ML and other data science solutions in a cloud-native, micro-service environment. AWS experience is a plus.
- 2-yrs experience writing Helm charts and Infrastructure as Code, with preference for Terraform/Terragrunt experience.
- Demonstrated proficiency in Python and SQL programming.
- Strong proficiency with software tools/practices such as Git, CI/CD pipelines, and integration testing.
- Experience creating APIs and other integration frameworks.
- Autonomous worker, able to define technical development themes/epics and user stories from business requirements and drive work to completion.
- A creative mind with excellent analytical, critical-thinking, and problem-solving skills that reliably demonstrates attention to details and accuracy in execution.
- Ability to independently and quickly learn and skill-up with unfamiliar data and/or products.
- Ability to thrive in both collaborative and independent work environments.
- Excellent communication skills in explaining engineering concepts and architecture and/or data flow diagrams to audiences with varying levels of experience.
