Data Scientist

At IBM Finance & Operations, we are the backbone of IBM's transformation driving efficiency, transparency, and smart decision-making across the business. Our teams provide the insight and discipline that guide strategy, ensure financial strength, and enable IBM to invest in innovation and growth. Working in Finance & Operations means combining analytical skills with collaboration and curiosity. You'll partner with colleagues across functions and geographies, using data, technology, and process excellence to create solutions that improve performance and deliver measurable impact. IBM offers continuous learning, career development, and a culture that values diverse perspectives. Join us and be part of a global team that keeps IBM moving forward, while building your own future in a dynamic and evolving environment. As a Data Scientist: Generalist, you will convert business problems into analytics solutions using your consulting skills and business knowledge. You will analyze client business issues, formulate hypotheses, and test conclusions to determine appropriate solutions methods. Your primary responsibilities will include: • Analyze Business Problems: Analyze client business issues, identify areas for improvement, and develop hypotheses to test and validate conclusions. This involves applying statistical techniques, modeling, and operations research to drive business insights. • Develop Analytics Solutions: Design and deploy analytics solutions that realize business value, exploring and examining data from multiple disparate sources to discover hidden insights and provide a competitive advantage. • Communicate Findings: Effectively communicate informed conclusions and recommendations to both business and IT leaders, influencing how the organization approaches business challenges. • Build Statistical Models: Develop and apply statistical models to extract insights from data, determining what it means and recommending ways to apply the data to drive business outcomes. • Explore and Examine Data: Extract, transform, and combine data from various sources to identify trends, patterns, and correlations that inform business decisions. • Statistics and Modeling Foundation: Exposure to statistics, modeling, operations research, computer science, and math to analyze business issues and develop analytics solutions. • Data Analysis and Interpretation: Experience working with data from multiple disparate sources to extract, transform, and combine data, discovering hidden insights and informing business decisions. • Business Acumen and Communication: Exposure to communicating findings and recommendations to both business and IT leaders, influencing how an organization approaches business challenges. • Analytics Solution Development: Experience with designing and deploying analytics solutions that realize business value, applying statistical techniques and modeling to drive business insights. • Data-Driven Problem Solving: Exposure to analyzing business problems, identifying areas for improvement, and developing hypotheses to test and validate conclusions. • Computer Science Knowledge: Exposure to computer science concepts and applications to analyze business issues and develop analytics solutions. • Math Foundation: Experience working with mathematical techniques to drive business insights and inform decision-making. • Operations Research Understanding: Exposure to operations research principles to optimize business processes and solve complex problems. United States Data & Analytics Hybrid Entry Level RESEARCH TRIANGLE PARK, US RESEARCH TRIANGLE PARK (0147) International Business Machines Corporation Analytics Business Insights Communication Computer Science Data Analysis Inform Modeling Operations Research Problem Solving Statistics Business Acumen Decision Making Influencing