A career in IBM Consulting is rooted in long-term relationships and close collaboration with clients across the globe.
You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio including Software and Red Hat.
Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. You will be encouraged to challenge the norm investigate ideas outside of your role and come up with creative solutions resulting in groundbreaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience.
During your co-op experience you can enhance your knowledge and gain professional experience by working on client projects. This role provides an exceptional opportunity to build a compelling portfolio acquire new skills gain insights into diverse industries and embrace novel challenges for your future career.
At IBM we prioritize continuous learning skill development and personal growth within a culture of coaching and mentorship. As a co-op you'll experience this culture and have the opportunity to 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.
- Data Integrations: Develop skills in writing efficient and reusable programs to cleanse integrate and model data. Evaluate model results contributing to data-driven insights.
- Effective Communication: Assist in conveying analytical results to both technical and non-technical audiences refining your ability to communicate complex findings.
- Tech-Driven Data Transformer: Utilize program 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 expanding your tech toolkit
These positions are anticipated to start in summer 2026.
Candidates must have the ability to obtain and maintain a Federal Security clearance while in IBM Federal Consulting.
The below requirements are guidelines. If you have transferable skills we encourage you to apply for this role.
- Currently pursuing a quantitative degree in Computer Science Statistics Mathematics Engineering IST or a related field.
- Strong Interpersonal skills that enhance collaboration and relationship building while also managing dynamic workloads in an agile environment.
- Have initiative and passion to actively seek new knowledge and improve skills while embracing a growth mindset to assimilate diverse viewpoints.
- Demonstrate leadership experience and ability to communicate effectively through active listening; while also be willing to adapt and have a 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 is a plus.
- Experience using machine-learning/data science libraries in python (scikit-learn SciPy pandas PyTorch) is a plus.