Data Scientist – Client Engineering

Introduction
At IBM we’re revolutionizing our approach to technology sales. Our Client Engineering teams are champions of co-creating solutions in real-time to solve complex business challenges.
As an AI Engineer within our Client Engineering team you’ll harness your unique skills and perspectives to engage in the development and deployment of AI systems using our watsonx platform creating 4-to-6-week pilots for clients and contributing to IBM’s story of growth and innovation.
In this role you’ll partner with technical leaders across IBM and drive client engagements with a curiosity that sparks innovation and learning. Your contributions will form a cornerstone in our sales strategy facilitating rapid client delivery and product innovation.
At IBM the possibilities are endless. We offer extensive onboarding and ongoing development fostering an environment where you can thrive and shape your own career trajectory. Surrounded by a supportive team you’ll be integral in creating user-centric compelling pilots that lead clients to continually invest in IBM’s people products and services.

Your Role and Responsibilities
IBM Technology Client Engineering provides speed-to-value and innovation for our clients. We embed the IBM Garage methodology into the sales cycle to co-create and co-execute an initial iteration of an MVP with the purpose to land and grow our hybrid cloud platforms and establish IBM’s technical eminence and expertise with our clients. We are a “demonstration and innovation team” that will prove IBM’s technology and services through co-creation. This Garage experience will validate the particular technology or solution approach that leads to meaningful business outcomes for the client and grows IBM’s hybrid cloud platform.

To be successful in this role of Data Engineer you will need to:

• Be familiar with Data Engineering techniques to gathers prepare cleanse and transforms client data for analysis and AI automation including automating data pipelines.
• Demonstrate strong business acumen and ability to understand business problems formulate hypotheses and test conclusions to influence solution design
• Leverage a variety of structured and unstructured data sources analytics AI tools and programming languages to derive meaningful data insights (e.g. Python R Spark TensorFlow Jupyter etc.)
• Possess relevant industry and/or business domain knowledge such as Finance or Health Care which you will apply to shape solutions
• Take a user-centric approach to design and creates compelling prototypes that lead to transformative change for the client
• Work in an Agile fashion iterating on the design to react to client feedback and demonstrate rapid progress
• Expand partnerships at all levels of the client organization to identify new opportunities for data science applications

Required Technical and Professional Expertise

• More than 1 years as a Data Engineer/Scientist with a deep understanding of Statistics and statistical practices
• At least 1 years of experience with identifying data sources transforming data (ETL) etc.
• Experience with a Data Science Programming language such as Python or R

Preferred Technical and Professional Expertise

• Basic understanding Docker or Kubernetes-Container
• Experience in AIOps/MLOps/DataOps is a plus
• Deep understanding of modern machine learning techniques and mathematical underpinning such as classifications recommendation systems optimization etc.
• Experience in working with data size from small volume to Terabyte