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.

Your Role and Responsibilities

• Enhance your knowledge and gain professional experience by working on client projects.
• Build a compelling portfolio, acquire new skills, gain insights into diverse industries, and embrace novel challenges for your future career.
• Experience a culture of continuous learning, skill development, and personal growth within a coaching and mentorship environment.
• 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.
• Demonstrate familiarity or interest in statistical analysis or data mining through previous internships, personal/academic projects, hackathons, and/or publications.
• Preferred majors: Data Science, AI, ML, Cognitive Science, Statistics or Engineering.
• General familiarity with databases, data-engineering tools (SQL, Spark, Snowflake) and cloud platforms (e.g., IBM Cloud, Azure, AWS).
• Familiarity with NLP/LLM/GenAI is a plus.
• Experience with eval-driven development of AI Agents, ML&AI Ops/Observability.
• Skills/Tech: Python, Development/Deployment with coding agents (Cursor, Claude Code, Codex, etc).
• Experience using machine-learning/data science libraries in python (scikit-learn, SciPy, pandas, PyTorch) is a plus.

Preferred Technical and Professional Experience

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