Poughkeepsie, United States Role overview
About this role
We are seeking a motivated and talented intern with a strong foundation in software development and data analytics to join our team. This position offers hands-on experience in software engineering, data science, and systems quality assurance within a collaborative and agile environment. As a Systems Assurance Data Scientist, you’ll contribute to assuring the 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) Data visualization for stakeholders (Development, Test, Manufacturing, Client Support… teams) for monitoring, early warning, corrective actions… Quality Metrics calculation and validation: MTBF, subsystem/part PPM rates 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 Server Systems Field install base Inventory Provide inventory data analytics (Features, Configurations, usage where available…) to Development, Portfolio Management Manage Parts data for Incidents and Part ppm tracking. Manage Quality Targets for all current Servers, subsystems, and parts. Skills we are Looking For Experience or coursework in software development, design, and/or testing Understanding of computer architecture and programming fundamentals 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 Experience with at least one programming language (e.g., Python, Java, SQL), demonstrated proficiency in Python; familiarity with JavaScript or React is a plus Familiarity with development tools such as Git/GitHub, Visual Studio Code, Eclipse Exposure to AI coding assistants (e.g., IBM Bob) Experience with Python data science and machine learning libraries such as scikit-learn, pandas, PyTorch etc. Understanding of data visualization tools and techniques Knowledge of basic statistics and data modeling concepts Ability to learn and deploy dashboard & visual charts using React or other javascript libraries. • Data Visualization Tools: Exposure to data visualization tools and technologies to effectively communicate insights and findings to stakeholders. • Machine Learning Concepts: Basic understanding of machine learning concepts and techniques to support data analysis and statistical modeling. • Programming Languages: Interest in programming languages, such as Python or R, to support data extraction, transformation, and combination.