Principal Data Scientist - Network Reliability Engineering - AI/ML

Oracle • Austin, TX

77d

About The Position

As a Principal Data Scientist, you will play a key role in designing, building, and maintaining the data infrastructure that powers statistical analyses and machine learning initiatives for the Network Reliability Engineering organization. You will work closely with data scientists, engineers, and other stakeholders to develop and deploy scalable, efficient, and reliable ETL data pipelines that drive business value. You will also lead initiatives to improve, deliver, and enable reporting and insights.

Requirements

• BS (or equivalent experience) in Data Science, Computer Science, Engineering, or a related quantitative or technical field
• 8+ years of data science or software engineering experience
• Expertise in data pipeline tools such as Apache Spark, Apache Beam, or Apache Flink
• Experience with data warehousing and data lake technologies such as Oracle Object Storage, Apache Hadoop, Apache Hive, or Amazon Redshift
• Strong programming skills in languages such as Python, Java, or Scala
• Solid understanding of data structures and algorithms for designing and implementing efficient, scalable data processing systems
• Experience with containerization technologies such as Docker and Kubernetes
• Experience analyzing data, generating insights, and telling stories with data
• Strong understanding of data governance, data quality, and data security principles
• Excellent communication and collaboration skills

Nice To Haves

• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Experience with cloud-based data platforms such as OCI, AWS, GCP, or Azure
• Experience with data visualization tools such as Oracle Analytics Cloud, Tableau, Power BI, or D3.js
• Experience with agile development methodologies and version control systems such as Git or Bitbucket

Responsibilities

• Design, build, and maintain large-scale ETL data pipelines to support statistical analyses and machine learning model training, testing, and deployment
• Collaborate with data scientists and other stakeholders to understand data needs and develop effective solutions
• Create comprehensive data strategies to enable reporting, analytics, and machine learning
• Conduct research to evaluate data and answer strategic business questions
• Generate actionable insights and enable reporting through data transformation, statistical analyses, and machine learning methods
• Fine-tune and optimize algorithms and models to ensure scalability, reliability, and high performance
• Develop and maintain data architectures that support data warehousing, data lakes, and data governance
• Work with cross-functional teams to integrate data pipelines
• Ensure data quality, integrity, and security across all data pipelines and systems
• Develop and maintain metrics and monitoring to ensure data pipeline performance and reliability
• Champion software engineering and data science principles
• Provide guidance and mentorship to junior data scientists, contributing to team knowledge and best practices
• Stay up-to-date with the latest developments in machine learning, statistics, and data science, applying new techniques to improve processes and products

What This Job Offers

• Career Level: Senior
• Education Level: Bachelor's degree
• Number of Employees: 5,001-10,000 employees