• Responsibilities including:
• Identify and propose new use cases.
• Break those use cases down into discrete MVPs (minimal viable product).
• Work in code notebooks
• Build and validate models
• Deploy models via APIs into applications or workflows.
• Monitor & retrain models
• Use code repositories to version and share code/notebooks.
• Visualise the output of their data story in a way that is consumable by all

Required Skills:

Position: Data Scientist

We live in a moment of remarkable change and opportunity. The convergence of data and technology is transforming industries and society. IBM HR IT Delivery plays a key role in developing and supporting IBM’s technology to be digital-ready.
The current opportunity is a role with the HR IT Delivery team, who promote a fresh and energetic approach to innovation, creativity, and solution architecture within the CIO. We heavily use advanced technology such as AI and ML (machine learning) and keep on pushing the boundaries. An approach that is borne out by many active projects within our team that have yielded several success stories to date. The principles of collaboration, knowledge sharing, and leadership are promoted within our team and are the foundations that enable motivated individuals with diverse skills to function as part of a highly productive and innovative team.

Required Technical and Professional Expertise

• Solid experience with Watson Studio and IBM Cloud (Cloud Pak for Data)
• Solid experience in using Python numerical and scientific libraries like numPy and sciPy.
• Outstanding expertise and hands-on experience on machine learning algorithms
• Experience of incorporating ML and AI concepts into product/service solutions with a focus on deep learning.
• 1+ year of experience working with machine learning pipelines—data ingestion, feature engineering, modelling, including ensemble methods, predicting, explaining, deploying, and diagnosing ML models.
• Knowledge in random forest, radiant boosting, statistical analysis, Jupiter notebooks, Watson Studio, etc. with innovative and creative ideas and a love of AI
• Experience in sharing data science/machine learning experiment results with both technical and business-orientated people.
• Innovative mindset and an ability to take calculated risks with a fallback plan in the back pocket.

Preferred Technical and Professional Expertise

• Machine learning pipeline: data ingestion, feature engineering, modelling, including ensemble methods, predicting, explaining, deploying, and diagnosing ML models.