We are seeking a motivated and talented recent college graduate with a foundation in business data analytics to join our team. This position offers hands-on experience in data science, and systems quality assurance within a collaborative and agile environment. The successful candidate will be responsible for owning critical programs and discovering ways to introduce AI technologies to gain efficiencies and better client quality.
As a Systems Assurance Data Scientist, you’ll contribute to assuring the quality, availability and reliability of IBM’s industry-leading Server technologies. Responsibilities such as but not limited to:
- Data analytics for:
- IBM Server Systems client impacting field event analysis (repairs, outages).
- System Telemetry data (diagnostics data)
- Client-specific analysis.
- Data visualization for stakeholders (Development, Test, Manufacturing, Client Support… teams) for monitoring, early warning, corrective actions…
- Quality Metrics calculation and validation.
- Provide analytics for surgical field corrective actions.
- Document and drive to closure issues impacting Server Systems quality
- Provide all applicable data analytics to prioritize higher impact (at client) and pervasive events
- Track the application of fixes in the Field
- Manage Quality Targets for all current Servers, subsystems, and parts.
- Experience or coursework in software development, design, or testing
- Strong interpersonal and communication skills
- Ability to work effectively in a dynamic, agile team environment
- Self-motivated with a growth mindset and eagerness to learn
- Leadership potential and ability to take ownership of tasks
- Exposure to AI coding assistants (e.g., Watsonx Code Assistant)
- Knowledge of basic statistics and data modeling concepts
- Ability to learn and deploy dashboard & visual charts using approved software.
- Computer Science Knowledge: Exposure to computer science concepts and applications to analyze business issues and develop analytics solutions.
- Math Foundation: Experience working with mathematical techniques to drive business insights and inform decision-making.
- Operations Research Understanding: Exposure to operations research principles to optimize business processes and solve complex problems.