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Your Role and Responsibilities The IBM Sustainability Software business unit is seeking a talented and motivated data scientist to work as a Data Scientist across our portfolio of software products. Our group helps companies turn their sustainability ambitions into actions by embedding AI into the software that they use for managing their supply chains, assets, complex engineering, and environmental intelligence processes. We work on problems for everything from predicting asset failures from IOT data to optimizing supply chain decisions to helping companies reduce their carbon footprint and understand the impacts of climate change on their business. You will work across the entire AI and software lifecycles including requirements gathering, use case definition, design, model building, implementation, testing, documentation, and delivery. You’ll frequently work with Product Owners, Architects, Designers, Sales, Support, Business Partners, and customers throughout this process. This is an exciting opportunity to work as a part of a worldwide team of data scientists on problems that really matter at a scale that few other companies can support
Required Technical and Professional Expertise
Total 6+ years experinece in Data/AI/Software development
4+ years of hands-on experience in the data science ecosystem including:
Hands-on experience with big data technologies (e.g., Spark, Ray) and deep learning frameworks (PyTorch, Tensorflow, Keras)
Hands-on experience with SQL and Python
Hands-on experience building libraries and packages to be re-used by others
Hands-on experience building DS Solutions for production usage
Excellent understanding of machine learning techniques and algorithms and their drawbacks
Team player with a problem-solving attitude
Experience in delivering advanced analytical projects to large, complex organizations in a multi-functional environment.
Able to challenge and review the quality and value generated from analytical outputs
Focus on driving business value for clients to support long-term relationships.
Preferred Technical and Professional Expertise
Expertise in vision, language models, optimization, or advanced machine learning techniques
Familiarity with with DevOps frameworks (Git, CI/CD, Docker)
Ability to clearly communicate complex ideas to different audiences
Independently contribute to projects or workstreams with limited guidance
Has developed new approaches to existing methods and technologies to develop and deploy solutions
Uses, implements, and shares knowledge and expertise to drive advances in project work
Makes contributions to the creation of IP in form of patents, publications, assets
Effectively coaches and at times manages the work of junior team members (including interns)