A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe.
You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat.
Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.
As an IBM data professional, you'll turn client data into business value by analyzing information, communicating results and collaborating on product development. Use visual and open source tools, as well as flexible and scalable deployment options. Solve real-world problems for innovative industries, focusing on cognitive applications and artificial intelligence to tackle business challenges. Your responsibilities include translating mathematical formulas into code, building proof-of-concept models and algorithms, and developing predictive mathematical models using artificial intelligence.
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Any degree related to Information Technology, Computer Engineering, Computer Science, Statistics, Mathematics or related areas.
Solid experience with:
- Knowledge of Statistics: descriptive statistics, diagnostics, probability distributions, hypothesis testing and Machine Learning.
- Programming in Python (libraries such as Pandas, Scikit-Learn, Stats Models, PySpark, Keras, PyTorch, TensorFlow).
- Data manipulation: interaction with databases and data manipulation using the SQL language.
- Data visualization.
- Code versioning (Git/Bitbucket).
- Cloud (Azure, AWS, Google Cloud, IBM Cloud).
- Experience with GenAI.
- Cloud certification.
- English