Associate AI & Analytics – Data Scientist-Finance Transformation 2026

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.

We are seeking a highly skilled Data Scientist to join our team in the AI industry. This role involves leveraging advanced analytics, machine learning, and statistical modeling to extract insights from large datasets and develop innovative AI-driven solutions. The ideal candidate will combine strong technical expertise with a passion for solving complex problems and driving data-informed decision-making.

Your Role And Responsibilities

• Design, develop, and implement machine learning models and AI algorithms to solve business challenges.
• Analyze large, complex datasets to identify patterns, trends, and actionable insights.
• Collaborate with cross-functional teams (engineering, product, and business) to integrate AI solutions into production systems.
• Perform data preprocessing, feature engineering, and model optimization for high performance and scalability.
• Conduct experiments and validate models using appropriate statistical techniques.
• Communicate findings and recommendations through clear visualizations and reports.
• Stay updated on emerging AI technologies, frameworks, and best practices.

We have positions open in these locations:

• Austin, TX
• Atlanta, GA
• Chicago, IL
• Dallas, TX
• Houston, TX
• Durham, NC
• New York, NY

Preferred Education

Bachelor's Degree

Required Technical And Professional Expertise

• 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.

Proven experience in machine learning, deep learning, and statistical modeling.

Proficiency in programming languages such as Python or R.

• Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques.
• Experience working with large datasets and distributed computing frameworks (e.g., Spark, Hadoop).
• Excellent problem-solving skills and ability to work in a collaborative environment.
• 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
• Experience in Natural Language Processing (NLP), Computer Vision, or Generative AI.
• Familiarity with cloud platforms (AWS, Azure, GCP) and MLOps practices.
• Strong understanding of data architecture and data engineering principles.
• Prior experience in the AI industry or related research projects.
• Experience with API development and integration for AI models.

Understanding of ethical AI principles and data privacy regulations.