Seeking new possibilities and always staying curious, we are a team dedicated to creating the world’s leading AI-powered, cloud-native software solutions for our customers. Our renowned legacy creates endless global opportunities for our IBMers, so the door is always open for those who want to grow their career.
IBM’s product and technology landscape includes Research, Software, and Infrastructure. Entering this domain positions you at the heart of IBM, where growth and innovation thrive
The Data Engineer role requires a highly analytical individual proficient in Python programming, database management, and data methodologies. You’ll focus on extracting insights from data, developing and implementing machine learning models, managing big data infrastructure, and supporting AI-driven product development.
Key Responsibilities:
- Data Collection and Cleansing: Collect and cleanse data from diverse sources to ensure high-quality datasets for decision-making.
- Data Exploration and Visualization: Explore and visualize data using advanced techniques to uncover insights and trends.
- Statistical Analysis: Apply statistical and mathematical techniques to provide robust analytical foundations for predictive modeling.
- Machine Learning and Deep Learning: Develop and implement machine learning and deep learning models to address business challenges.
- ML-Ops / AI-Ops: Demonstrate expertise in ML-Ops / AI-Ops practices to ensure efficient model deployment and management.
- Big Data Management: Manage big data infrastructure and execute data engineering tasks for efficient data processing.
- Version Control and Collaboration: Utilize version control systems like Git for maintaining codebase integrity and fostering collaboration.
- AI-Driven Product Development: Design, create, and support AI-driven products to deliver impactful solutions aligned with user needs and business objectives.
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