Implement data science algorithms in bpx’s ML Studio (SageMaker)
Create systems and processes to monitor performance of ML algorithms in production
Serve as the subject matter expert of ML Operations and guides data scientists in the practical implications of model design
Collaborate with the data engineering team to build and maintain data pipelines from systems like Snowflake and OSI Pi
Partner with bpx Architecture team to ensure endpoints, compute, and network considerations are built into solutions
Takes initiative and stays up to date with the latest data science trends, techniques, and best practices, determining how to incorporate the most suitable practices in the department
Work as part of geographically dispersed team, effectively communicating prioritized business needs and prioritized project statuses
Design systems to balance cost and performance to meet business outcomes

A Bachelor’s degree (Master’s preferred) in Statistics, Mathematics, Computer Science, or any other related quantitative field
7+ years in data science or related field, 3+ years of hands-on experience in machine learning operations
Proven track record of implementing and scaling models in an operations or customers focused company
Strong programming skills: Python and Cloud Implementation
Scripting Experience with big data, real-time streaming data technologies, and cluster computing environments
Knowledge and exposure to cloud technologies, especially AWS
Must be legally authorized to work in the US without sponsorship.

Machine Learning Engineer

Key skills