The Data Science team at Oracle Analytics is at the forefront of solving complex business challenges using cutting-edge machine learning (ML) and artificial intelligence (AI) techniques. Our focus is on enterprise data analytics, tackling real-world problems such as invoice payment prediction, churn analysis, demand forecasting, and recommender systems. Leveraging a diverse set of technologies including text processing, information retrieval, natural language processing (NLP) with large language models (LLMs), and time series prediction, we strive to create intelligent, data-driven solutions for businesses worldwide.
As a key member of our team, you will be responsible for developing and deploying state-of-the-art ML models, working on data engineering pipelines, and conducting insightful analyses that drive strategic decision-making. You will collaborate with cross-functional teams, including product managers, engineers, and business stakeholders, to translate complex data challenges into actionable insights and solutions.
Key Responsibilities
- Conduct in-depth research on existing literature, research papers, and emerging trends in relevant problem domains to inform model development.
- Perform data preprocessing, cleansing, and verification to ensure data integrity and usability for ML applications.
- Carry out exploratory data analysis (EDA) and create meaningful visualizations to uncover trends, anomalies, and insights.
- Develop and fine-tune machine learning models using frameworks such as PySpark, Scikit-learn, TensorFlow, Keras, and PyTorch.
- Work on building and optimizing scalable data pipelines for deploying ML models using platforms like Oracle DataFlow.
- Implement and maintain post-deployment monitoring of ML models, ensuring their accuracy, efficiency, and adaptability over time.
- Collaborate with product and service teams to identify key business questions and design data-driven solutions that drive innovation and efficiency.
- Develop and code software programs, algorithms, and automated processes to extract, clean, integrate, and analyze large datasets from multiple sources.
- Interpret and communicate insights from data analysis, experiments, and ML models to product, service, and business managers in a clear and actionable manner.
Required Skills & Qualifications
- Strong programming skills in Python and PySpark, with hands-on experience in building and deploying ML models in Spark environments.
- Solid understanding of machine learning algorithms, statistical modeling, and AI techniques.
- Experience with data manipulation, feature engineering, and working with large-scale datasets.
- Knowledge of cloud-based ML deployment techniques, particularly within Oracle Cloud or similar platforms.
- Ability to conduct independent research and stay updated with the latest advancements in AI and ML.
- Strong problem-solving skills with the ability to work on ambiguous and challenging data problems.
- Excellent communication and collaboration skills, with experience working in cross-functional teams.
- Prior industrial experience in data science and machine learning is highly desirable.
About Oracle
Oracle is a global leader in cloud solutions, leveraging tomorrow’s technology to address today’s most pressing challenges. Innovation is at the heart of what we do, driven by a commitment to diverse perspectives and inclusive workforce culture.
For over 40 years, Oracle has been pioneering advancements in cloud computing, AI, and enterprise solutions, empowering organizations worldwide to harness the power of data. Our partnerships span across industries, ensuring that businesses of all sizes can scale, innovate, and succeed.
We believe in fostering an environment where employees thrive. Our work culture emphasizes work-life balance, professional growth, and continuous learning. We offer a comprehensive benefits package, including flexible medical, life insurance, and retirement plans, along with opportunities for community involvement through volunteer initiatives.