Director, Data Science & Machine Learning Operations (ML Ops)
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Help shape the future of Data Science across Liberty!
As Director of Machine Learning Operations (MLOps) in the Office of Data Science (ODS), you will work with a diverse group of data scientists and engineers to broadly influence how we train, package, investigate, and deploy machine learning models and other data science artifacts at Liberty. You will be ingrained with all aspects of how we operationalize data science, from broad team and staffing strategies, to tool selection and architectural design, and helping or supervising the deployments for some of our keystone projects.
The ODS was created to provide additional centralized support and expertise to DS teams across the global organization. Our projects focus on key areas of interest to multiple teams: bleeding edge research and experimentation, common tool and platform development, and establishing best practices to ensure the scientific community at Liberty is well-positioned to rapidly meet the challenges of modern industry.
As a technical director of Machine Learning Operations, you will be responsible for setting the scientific strategy for many of these how's, tactically engaging with key groups to determine the mechanics of training and deploying models, and working with our platform teams to build or adopt repeatable tools and packages. You will help us vet modern tools like AWS Sagemaker, MLFlow, Seldon, and others to determine what works for Liberty and what we need to build. You will help operationalize numerous models across the organization, provide guidance and training to DS and engineers alike, and set the standard for applied machine learning at Liberty.
As a centralized group, our project scope is vast. The ODS incubates a number of ML projects, as well as collaborating on larger projects across the org, in many areas including advanced predictive modelling, computer vision, natural language processing, and more. Our group excels in the how' of data science how to write repeatable code, how to train a model continuously, and how to package and deploy it into a production system. If you are interested in making an impact on an entire scientific culture at a Fortune 100 company, the ODS is the place for you!
- Demonstrated experience with the mechanics of training and deploying ML models, as well as other aspects of the Data Science lifecycle, such as scheduling, CI/CD, cluster computing, serverless architectures, etc.
- Experience bridging the gap between engineering and data science groups
- Broad knowledge of machine learning and statistics, with the ability to deep dive as well as converse at high technical level with architects and senior scientists. NLP/NLU, Computer Vision, and other deep learning experience a plus.
- Advanced python and related programming skills
- Experience directing or managing small to medium projects
- Ability to give effective training and presentations to DS and engineers
- Advanced degree and 5 to 7 years of relevant experience, or a Bachelor`s degree with 10 years of relevant experience