Data Engineer - Advanced Analytics

**Introduction** A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. **Your role and responsibilities** As a Data Engineer with Advanced Analytics expertise, you will specialize in formulating mathematical approaches to solve complex business problems and utilize predictive analytics tools to draw conclusions and present findings. You will design, build, and manage solutions that involve preparing data, performing statistical analysis, and deploying analysis results. Your primary responsibilities will include: - Design and Build Solutions: Design, build, and manage solutions that involve preparing data, performing statistical analysis, data collection, data mining, and text mining, and deploying analysis results. - Perform Statistical Analysis: Perform statistical analysis and utilize predictive analytics tools like SPSS to draw conclusions and present findings. - Prepare Gather and prepare data for advanced analytics projects, ensuring data quality and integrity. - Apply Mathematical Optimization: Apply mathematical optimization, discrete-event simulation, and rules programming to solve complex business problems. - Deploy Analysis Results: Deploy analysis results and present findings to stakeholders, providing insights and recommendations for business improvement. **Required technical and professional expertise** - Data Engineering Principles: Exposure to data engineering principles and their application to advanced analytics projects, enabling the design, build, and management of effective solutions. - Predictive Analytics Tools: Experience working with predictive analytics tools like SPSS to perform statistical analysis, draw conclusions, and present findings. - Mathematical Optimization: Exposure to mathematical optimization, discrete-event simulation, and rules programming to solve complex business problems. - Data Preparation: Experience working with data preparation techniques to ensure data quality and integrity for advanced analytics projects. - Statistical Analysis: Exposure to statistical analysis and data mining techniques to extract insights and inform business decisions. **Preferred technical and professional experience** - Predictive Modeling Techniques: Exposure to predictive modeling techniques, such as regression, decision trees, and clustering, to enhance advanced analytics capabilities. - Data Visualization Tools: Experience working with data visualization tools to effectively communicate insights and findings to stakeholders. - Machine Learning Algorithms: Exposure to machine learning algorithms, such as neural networks and random forests, to expand analytical capabilities. 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.