We are in a data science renaissance.Companies that embrace data science will lead and those who do not will fall behind.
To help IBM's clients lead, we are building a team of data science practitioners to help them learn how to succeed with data science.
The team will include data engineers, machine learning engineers, operations research / optimization engineers and data journalists.
The team will engage directly in solving real-world data science problems in a wide array of industries around the globe with IBM clients and internally to IBM.
The team of data scientist will work with other IBMers and client data science teams to solve problems in banking, insurance, health care, manufacturing, oil & gas and automotive industries, to name a few.
We will teach the data scientists and sometimes people who desire to be data scientist to : Key Responsibilities : 1. Identify a use case2.
Break that use case down into discrete MVPs (minimal viable product)3. Work in code notebooks4. Build & validate models5.
Deploy models via APIs into applications or workflows6. Monitor & retrain models7. Use code repositories to version and share code / notebooks8.
Visualize the output of their data story in a way that is consumable by all9. Create Machine Learning pipelines and train models.
10. Communicate effectively with line-of-business end-users to discover pain points and use cases, lead project definitions, and convey the business value of the projectWhile working across all these industries, you will also get to travel as these engagements may require that the team spend several weeks at client sites working on data science problems with a diverse team.