Data Scientist

**Introduction** 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. **Your role and responsibilities** As a Data Scientist: Analytics, you will work with clients and industry experts to frame problems, analyze data, apply machine learning technologies, and develop predictive insights. You will provide client-facing services for IBM's next-generation cognitive predictive analytics solution, delivering insights powered by Watson Analytics. Your primary responsibilities will include: • Analyze Client Data: Work with clients to analyze their data, identify patterns, and develop predictive insights to help them address business problems, predict the future, or take action. • Apply Machine Learning: Apply machine learning technologies to client data to develop predictive models and deliver insights that drive business outcomes. • Frame Problems: Collaborate with clients and industry experts to correctly frame problems and identify opportunities for data-driven solutions. • Develop Predictive Insights: Use data science techniques and models to develop predictive insights that help clients make informed business decisions. • Deliver Client Solutions: Provide client-facing services, delivering insights and solutions that meet client needs and expectations. **Required technical and professional expertise** • Deep Experience in Data Science: Proven expertise in one or more areas of data science, with broad exposure to various data science techniques and models. • Expert Tool Usage: Skilled in using SPSS or similar tools at an expert level, with ability to leverage IBM tools and general data science models. • Machine Learning Application: Experienced in applying machine learning technologies to develop predictive models and deliver insights that drive business outcomes. • Data Analysis and Insight Development: Adept at analyzing data, identifying patterns, and developing predictive insights to inform business decisions. • Exposure to Cognitive Predictive Analytics: Familiarity with cognitive predictive analytics solutions, such as those powered by Watson Analytics, and ability to deliver client-facing services. **Preferred technical and professional experience** Advanced capability in at least one programming language, preferably Python. JavaScript is also relevant. Experience developing automation solutions, such as RPA, workflow automation, scripts, process automation, backend automation, or similar automation use cases. Consuming APIs, Developing APIs, Designing APIs, Authentication, API Gateways Containerization, Orchestration, Cirrus Version Control / Git, CI/CD, Cloud Platforms, Monitoring & Logging IBM is committed to creating a diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender, gender identity or expression, sexual orientation, national origin, caste, genetics, pregnancy, disability, neurodivergence, age, veteran status, or other characteristics. IBM is also committed to compliance with all fair employment practices regarding citizenship and immigration status.