20 days old

Program Director - Data Science Elite, Asia Pacific

Singapore, CENTRAL SINGAPORE
  • Job Code
    198000BR
Job Description
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:


Key Responsibilities:
  • 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 clients to become self-sufficient data science practitioners
Required Professional and Technical Expertise:
  • At least 5 years experience - Computer Science, Programming skills
  • At least 5 years experience - Probability and Statistics
  • At least 4 years experience - Data Modeling and Evaluation
  • At least 4 years experience - Big Data and Machine Learning
Preferred Professional and Technical Expertise:
  • At least 7 years experience - programming skills in at least two of the following: Python, R, Scala or Java. preference for Python Expert
  • At least 5 years experience - Ability to consume and deploy data via APIs
  • At least 4 years experience - in applying supervised, unsupervised and semi-supervised learning techniques.
  • At least 4 years experience in Machine Learning pipeline - data ingestion, feature engineering, modeling including ensemble methods, predicting, explaining, deploying and diagnosing over fitting
  • At least 5 years experience - in model selection and sampling
  • At least 2 years experience - deep learning and neural nets
  • At least 5 years experience - Business and Leadership

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 well as leading a data science team at the client site.

Because of team organization and the nature of customer engagements, a high level of independence and a self-started attitude are needed.



Required Technical and Professional Expertise

  • Please refer to job description.


Preferred Tech and Prof Experience

  • Please refer to job description.


EO Statement
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.

Categories

Industry

  • Computers Software and Hardware
Posted: 2019-04-29 Expires: 2019-05-29

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Program Director - Data Science Elite, Asia Pacific

IBM
Singapore, CENTRAL SINGAPORE

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