Data Scientist Co-op 2026 – Advanced Analytics – Financial Services

Introduction

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 for success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions that result in ground-breaking 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.

Your Role And Responsibilities

During your co-op, 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 could 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.

Required Technical And Professional Expertise

* Currently pursuing a quantitative degree in Computer Science, Statistics, Mathematics, Engineering, 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

Preferred Technical And Professional Experience

* Preferred majors: Data Science, AI, ML, Cognitive Science, Statistics or Engineering

* 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, Snowflake) and cloud platforms (e.g., IBM

Cloud, Azure, AWS). *Experience with NLP/LLM/GenAI is a plus

* Experience: familiarity with eval-driven development of AI Agents, ML&AI Ops/Observability

* Skills/Tech: Python, Development/Deployment with coding agents (Cursor, Claude Code, Codex, etc)

* Ethics/governance awareness, ability to translate business use cases into models

* Experience using machine-learning/data science libraries in python (scikit-learn, SciPy, pandas, PyTorch) is a plus