Lead Applied Data Scientist

Oracle Corporation is seeking a Lead Applied Data Scientist to join their SaaS Engineering team in an exciting new initiative focused on advancing service reliability through AI agents. This role sits at the intersection of cutting-edge AI/ML and cloud infrastructure, working to develop sophisticated systems that can predict and autonomously resolve issues before they impact cloud services.

The position requires a seasoned professional with 10+ years of experience who can lead complex data science projects from conception to deployment. The ideal candidate will have deep expertise in machine learning, particularly in areas like anomaly detection and predictive modeling, with strong proficiency in Python, R, and modern ML frameworks including TensorFlow and PyTorch.

As a Lead Applied Data Scientist, you'll be responsible for spearheading the development of sophisticated machine learning models for anomaly detection in system logs, conducting in-depth analysis of large-scale time-series data, and mentoring junior team members. The role combines technical leadership with hands-on development, requiring both strong analytical skills and the ability to communicate complex technical concepts to various stakeholders.

The position offers a competitive salary range of $139,300 to $291,900 per annum, along with comprehensive benefits including medical, dental, and vision insurance, 401(k) with company match, flexible vacation, and stock purchase options. Oracle provides a collaborative environment where innovation is encouraged and work-life balance is valued.

This is an exceptional opportunity for a senior data scientist looking to make significant impact in cloud service reliability while working with cutting-edge AI technologies at one of the world's leading technology companies. The role offers the chance to shape the future of cloud service resilience while working with a talented team in a supportive environment that promotes growth and innovation.