IBM Hiring Co-Op Data Scientist - AI & Analytics

Job Description

A career in IBM Consulting is built on long-term relationships and close collaboration with clients worldwide. You'll work with visionaries across multiple industries to enhance the hybrid cloud and AI journey for the most innovative companies. Your ability to accelerate impact and create meaningful change is supported by our strategic partner ecosystem and robust technology platforms across the IBM portfolio, including Software and Red Hat. Curiosity and a constant quest for knowledge are the foundation of success in IBM Consulting. You'll be encouraged to challenge norms, explore ideas beyond your role, and develop creative solutions that deliver groundbreaking impact for a wide network of clients. Our culture of evolution and empathy focuses on long-term career growth and development in an environment that values your unique skills and experience. To maximize your chances, we advise applying only to roles that align with your skills and experience, rather than applying broadly across all entry-level positions. You'll receive a status update email for each application, so check your IBM Careers account regularly for a centralized view of your active applications.

During your co-op, you'll enhance your knowledge and gain professional experience by working on client projects. This role offers an exceptional opportunity to build a compelling portfolio, acquire new skills, gain industry insights, and embrace novel challenges for your future career. At IBM, we prioritize continuous learning, skill development, and personal growth within a coaching and mentorship culture. As an intern, you'll experience this culture and may advance to our associate program based on results and performance.

Work experiences you could be exposed to:

• Mentored Analytical Support: Receive mentorship from diverse professionals in science, engineering, and consulting, applying analytical rigor and statistical methods to predict behaviors.
• Generative Artificial Intelligence (AI): Work with experienced practitioners to implement generative AI models and algorithms for applications like conversational computing, natural language processing, and audio processing. Use large datasets to train and evaluate generative models, optimizing their performance with various techniques.
• Data Integrations: Develop skills in writing efficient and reusable programs to clean, integrate, and model data. Evaluate model results to contribute to data-driven insights.
• Tech-Driven Data Transformer: Use programming languages like Python to build data pipelines, extracting and transforming data from repositories to consumers. Gain exposure to cloud platforms, ETL tools, and data integration.
• Effective Communication: Assist in conveying analytical results to both technical and non-technical audiences, refining your ability to communicate complex findings.

Qualifications:

• Currently pursuing a quantitative degree in Computer Science, Statistics, Mathematics, Engineering, IST, or a related field with an anticipated graduation date of May 2026 or later.
• Strong interpersonal skills that enhance collaboration and relationship building, while managing dynamic workloads in an agile environment.
• Initiative and passion to actively seek new knowledge and improve skills, embracing a growth mindset to assimilate diverse viewpoints.
• Demonstrated leadership experience and effective communication through active listening; willingness to adapt and readiness to take ownership of tasks and challenges.
• Familiarity with one or more scripting languages (Python preferred), or a proven computer science foundation.
• Ability to work in-office, on-site in State College, PA during the academic year.
• Ability to work up to 20 hours per week when classes are in session (e.g., fall and spring semesters) and availability to potentially work up to 40 hours per week during academic breaks (e.g., summer).
• Must have the ability to obtain and maintain a Federal clearance, if necessary, for your client assignment.
• Demonstrate familiarity or interest in statistical analysis or data mining through previous internships, personal/academic projects, hackathons, and/or publications.
• General familiarity with databases, data-engineering tools (SQL, Spark) and cloud platforms (e.g., IBM Cloud, Azure, AWS). Experience with NLP/LLM/GenAI (AutoGen, LangGraph, LangChain, watsonx Orchestrate, OpenAI) is a plus.
• Experience using machine-learning/data science libraries in Python (scikit-learn, SciPy, pandas, PyTorch) is a plus.