IBM Senior Data Scientist in NEW YORK, New York

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 clients learn how to succeed with data science. The team includes data engineers, machine learning and deep 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. The elite team of data scientists 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 are looking for a Principal Data Scientist for this team. This is a leadership role, where the individual will lead multiple squads in client engagements. This person should have a balance of strong Data Science skills and executive client-facing experience.

Key Responsibilities:

Lead Data Science Engagements with Clients

  1. Communicate effectively with line-of-business executives and end-users to understand use cases, lead project definitions, and convey business value of the project

  2. Identify a use case

  3. Break that use case down into discrete sprints

  4. Work in code notebooks

  5. Create Machine Learning pipelines and train models.

  6. Build & validate models

  7. Deploy models via APIs into applications or workflows

  8. Monitor & retrain models

  9. Use code repositories to version and share code/notebooks

  10. Visualize the output of their data story in a way that is consumable by all

  11. Guide and mentor clients to become self-sufficient data science practitioners

  12. Guide and mentor junior members of the IBM team

Work Locations: New York (preferred) and San Francisco

While working across all these industries, you will also get to travel the world as these engagements will require meeting clients, as well as leading a data science team at the client site.

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 / Deep Learning.

Required Technical and Professional Expertise

  • At least 10 years experience - Computer Science, Programming skills

  • At least 10 years experience - Data and Analytics

  • At least 5 years experience – Machine Learning and Deep Learning

  • Demonstrated C-Level customer interaction skills

  • Solid Business Acumen

Preferred Tech and Prof Experience

  • At least 10 years experience - programming skills in at least two of the following: Python, R, Scala or Java. Preference for Python

  • At least 5 years experience - in applying supervised, unsupervised and semi-supervised learning techniques

  • At least 5 years experience – Machine Learning pipeline - data ingestion, feature engineering, modeling including ensemble methods, diagnosing over-fitting, predicting, explaining, deploying etc.

  • 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 – Big Data, Hadoop, Spark

  • At least 10 years experience - Business and Leadership

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.