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 an elite 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 elite 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:
Identify a use case
Break that use case down into discrete MVPs (minimal viable product)
Work in code notebooks
Build & validate models
Deploy models via APIs into applications or workflows
Monitor & retrain models
Use code repositories to version and share code/notebooks
Visualize the output of their data story in a way that is consumable by all
Create Machine Learning pipelines and train models.
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 project
Guide and mentor clients to become self-sufficient data science practitioners
Guide and mentor more junior team members
Lead and define client projects, including technical leadership of small teams of 3-5 team members.
Participate actively in business development activities, such as public speaking engagements, participating in client events, and networking across IBM globally.
While working across all these industries, you will also get to travel the World as these engagements will require that the team spend several weeks at client sites working on data science problems with a diverse team.
As a member of the team you will have a T-shaped skill set, having a broad knowledge base in Data Science and Industry Solutions in general, but also in- depth expertise in Machine Learning / Data Science / AI.
Work Location: Boeblingen (near Stuttgart) or Munich
75% travel required
Required Technical and Professional Expertise
Masters' or PhD Degree in applied mathematics, computer science, engineering or related, preference for advance degree
Proficient programming skills, python preferred
Masters' + 4 years' work experience, OR PhD + 2 years' work experience
Big Data expertise
Preferred Tech and Prof Experience
Proficient programming skills in at least two of the following: Python, R, Scala or Java. preference for Python
Ability to consume and deploy data via APIs
Expert in applying supervised, unsupervised and semi-supervised learning techniques
Expert with ML pipeline - data ingestion, feature engineering, modeling including ensemble methods, predicting, explaining, deploying and diagnosing over fitting
Expert in model selection and sampling
Experience with deep learning and neural nets
Business experience and/ or leadership experience
Excellent communication skills
Fluent in English
Basic German language skills preferred
IBM is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.