Introduction
As a Data Scientist at IBM, you will help transform our clients' data into tangible business value by analyzing information, communicating outcomes and collaborating on product development. Work with Best in Class open source and visual tools, along with the most flexible and scalable deployment options. Whether it's investigating patient trends or weather patterns, you will work to solve real world problems for the industries transforming how we live.

Your Role and Responsibilities

At IBM, we are committed to leveraging cutting-edge technology and data-driven insights to deliver exceptional solutions across our business operations. The IBM CIO plays a critical role in accelerating our business and technology platform transformation and increasing the productivity of every IBMer using AI-powered technology.

• Collaborate with business leaders, engineers, and analysts to define and prioritize data-related opportunities
• Work closely with data engineers to ensure data availability, quality, and integration for data science initiatives
• Extract, compile, and validate data, conducting analysis using standard analytic and/or data science tools and techniques
• Work with senior data scientists and CIO leadership on analysis projects and support their data needs
• Assist in the development of automated reports and dashboards
• Build and maintain scalable data pipelines and machine learning models in production environments
• Continuously explore emerging technologies and methodologies in AI, machine learning, and data science to accelerate IBM CIO transformation

• 3+ years' experience with a programming language and/or statistical tool (R or Python preferred)
• 3+ years' experience with performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement
• 3+ years' experience working with data visualization or dashboarding tools (Cognos Analytics or Tableau)
• Strong analytic skills related to working with structured and unstructured datasets
• 3+ years' experience with core statistical analysis skills (e.g., linear regression, logistic regression, k-means clustering, significance testing, etc.)
• Working experience with generative AI techniques to develop innovative solutions for enterprise industry use cases
• Proven ability to translate business challenges into data science solutions
• Excellent communication skills and the ability to work effectively with both technical and non-technical stakeholders
• Strong analytical abilities and problem-solving skills and an informed, evidence-based approach
• Degree in statistics, mathematics, data/computer science, physics or another quantitative field. Quantitative degrees in social sciences (political science, sociology, psychology, etc.) are also acceptable
• Ability to manipulate, process, and extract value from disconnected datasets

• Proficiency in Machine Learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch), LLMs (e.g. IBM Granite, IBM Slate, Llama), and NLP/GenAI tools (e.g., HuggingFace, LangChain)
• Experience with SQL and relational databases
• Experience with cloud platforms for data science projects
• Familiarity with DevOps practices, CI/CD pipelines, and MLOps tools
• Previous experience in large-scale enterprise IT environments
• 2+ years' experience in research and/or experimental design
• Strong experience with big data framework such as Spark
• Experience with Iceberg: a high-performance format for large analytic tables
• Curiosity for exploring complex problems through analytics and insights
• Experience supporting and working with cross-functional teams in a dynamic (e.g., Agile) environment