Consulting Data Scientist 4.

Responsibilities 

• Design, build, and maintain large-scale data pipelines that support statistical analyses and machine learning model training, testing, and deployment 
• Collaborate with data scientists and other stakeholders to understand data needs and develop solutions that meet those needs 
• Create comprehensive data strategy 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, or machine learning methods 
• Fine-tune and optimize algorithms and models to ensure scalability, reliability, and performance at a high level 
• 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 

 Qualifications & Skills 

• BS (or equivalent experience) in Data Science, Computer Science, Engineering, or 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 different data structures and algorithms to design and implement efficient and 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  

Preferred Qualifications 

• Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-lear 
• 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 

 

Career Level - IC4

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Oracle is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Oracle will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. 

This role is part of an elite overlay consulting organization providing expert-level solution building and product knowledge to support Oracle Health’s strategic engagements. As a Principal Data Scientist, you will play a key role in solving complex challenges utilizing Oracle’s best-in-class AI and Gen AI applications, services, and infrastructure. The preferred candidate will have strong background in statistical analysis and machine learning. You will work closely with other data scientists, AI architects, developers, and other stakeholders to develop and deploy scalable, efficient, and reliable solutions that drive business value, while leading initiatives to improve, deliver, and enable reporting and insights. This role will require that you obtain and maintain Federal Security clearance as a US-based citizen.