Job Description

The Oracle Guided Learning development team is responsible for designing, developing, and maintaining world class Digital Adoption Platform (DAP) that serves millions of employees world-wide. As a member of the OGL development team, you will work with global colleagues to create modern, robust, scalable applications. In addition to technical and programming talent, our developers need to be customer focused, exhibit excellent communication skills, work well in a global team environment, be self-motivated and be willing to take on varied tasks to ensure the success of our projects. Excellent command of spoken and written English is essential.


We are seeking a highly motivated and skilled Data Scientist to join our dynamic team. The ideal candidate will have a strong background in statistical analysis, machine learning, and data manipulation. As a Data Scientist, you will work closely with cross-functional teams to analyze large datasets, develop predictive models, and provide actionable insights that drive strategic decision-making. Requirements:


• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field (Master's or PhD preferred).
• Proven 5-8 year experience as a Data Scientist or in a similar role.
• Strong programming skills in Python, R, or other relevant languages.
• Proficiency in SQL and experience with relational databases.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Knowledge of data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
• Solid understanding of statistical analysis and predictive modeling techniques.
• Excellent problem-solving skills and attention to detail.
Confident team player, with outstanding verbal and written communications skills.
•

Career Level - IC3



• Analyze large, complex datasets to extract meaningful patterns and insights.
• Develop, implement, and optimize machine learning models to solve business problems.
• Collaborate with stakeholders to understand business requirements and translate them into data solutions.
• Perform exploratory data analysis and data visualization to communicate findings effectively.
• Design and conduct experiments to validate hypotheses and improve models.
• Utilize data mining techniques to discover trends and patterns in data.
• Work with engineering teams to deploy data-driven solutions into production.
• Continuously monitor and improve the performance of deployed models.
• Present findings and recommendations to both technical and non-technical audiences.