Principal Data Scientist
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.
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
Qualifications & Skills
- 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
Preferred Qualifications
- 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
Disclaimer: Certain US customer or client-facing roles may be required to comply with applicable requirements, such as immunization and occupational health mandates. Range and benefit information provided in this posting are specific to the stated locations only.
US: Hiring Range in USD from: $96,800 to $223,400 per annum. May be eligible for bonus and equity. Oracle maintains broad salary ranges for its roles in order to account for variations in knowledge, skills, experience, market conditions and locations, as well as reflect Oracle's differing products, industries and lines of business. Candidates are typically placed into the range based on the preceding factors as well as internal peer equity. Oracle US offers a comprehensive benefits package which includes the following:
- Medical, dental, and vision insurance, including expert medical opinion
- Short term disability and long term disability
- Life insurance and AD&D
- Supplemental life insurance (Employee/Spouse/Child)
- Health care and dependent care Flexible Spending Accounts
- Pre-tax commuter and parking benefits
- 401(k) Savings and Investment Plan with company match
- Paid time off: Flexible Vacation is provided to all eligible employees assigned to a salaried (non-overtime eligible) position. Accrued Vacation is provided to all other employees eligible for vacation benefits. For employees working at least 35 hours per week, the vacation accrual rate is 13 days annually for the first three years of employment and 18 days annually for subsequent years of employment. Vacation accrual is prorated for employees working between 20 and 34 hours per week. Employees working fewer than 20 hours per week are not eligible for vacation.
- 11 paid holidays
- Paid sick leave: 72 hours of paid sick leave upon date of hire. Refreshes each calendar year. Unused balance will carry over each year up to a maximum cap of 112 hours.
- Paid parental leave
- Adoption assistance
- Employee Stock Purchase Plan
- Financial planning and group legal
- Voluntary benefits including auto, homeowner and pet insurance
The role will generally accept applications for at least three calendar days from the posting date or as long as the job remains posted. Career Level - IC4