Predictive Modeling Lead
3 weeks ago
Oracle's 'SaaS Engineering' team is setting up an exciting new team to work on advances in service reliability with teams of autonomous AI agents. The goal is to develop a robust system using advanced ML/AI tools to analyze system logs, predict failures, and autonomously resolve issues before they impact cloud services. This initiative combines cutting-edge domains of anomaly detection and autonomous agents to enhance service resiliency.
About the Role
As a Machine Learning Architect, you will be responsible for designing and implementing machine learning models that can predict service failures and autonomously resolve issues before they impact cloud services. You will work closely with cross-functional teams to align on project goals and deliverables.
Key Responsibilities
- Design and implement sophisticated machine learning models for anomaly detection in system logs
- Conduct in-depth analysis of large-scale, time-series data to identify patterns and anomalies
- Utilize statistical methods and machine learning techniques to develop predictive models that can preemptively address potential issues
Requirements
- 8+ years of experience in data science with a strong focus on machine learning and predictive modeling
- Strong expertise in Python and R programming languages, with a deep understanding of machine learning algorithms such as LSTM, GRU, and Transformers
- Proven track record of working with large datasets and big data technologies, including Hadoop and Spark
- Excellent leadership skills with a proven ability to mentor and guide junior team members
Compensation and Benefits
The estimated salary for this role is $139,300 - $291,900 per annum, depending on location and experience. Oracle offers a comprehensive benefits package, including medical, dental, and vision insurance, short-term disability and long-term disability, life insurance, and AD&D, among others.
About Us
As a world leader in cloud solutions, Oracle uses tomorrow's technology to tackle today's problems. We're committed to expanding our inclusive workforce that promotes diverse insights and perspectives.
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