Data Engineer-Machine Learning - 1

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. As a Data Engineer with expertise in Machine Learning, you will apply Machine Learning concepts and techniques to address business challenges. You will leverage your skills to drive informed decision-making in the organization. Your primary responsibilities will include: • Develop Machine Learning Solutions: Design and implement Machine Learning models to solve complex business problems, selecting relevant features and algorithms to achieve desired outcomes. • Evaluate Algorithm Performance: Assess the effectiveness of Machine Learning algorithms using relevant metrics, identifying areas for improvement and optimizing model performance. • Interpret Statistical Data: Analyze and interpret complex statistical data to inform business decisions, communicating insights and recommendations to stakeholders. • Communicate Results: Clearly articulate the results of Machine Learning initiatives, providing actionable insights and recommendations to drive business outcomes. • Drive Informed Decision-Making: Collaborate with stakeholders to integrate Machine Learning insights into business decision-making processes, driving informed strategic choices. This role can be performed from anywhere in the United States of America. • Deep Expertise in Machine Learning: Proven ability to apply Machine Learning concepts and techniques to address complex business challenges, leveraging expertise in algorithm selection, feature engineering, and model optimization. • Experience with Statistical Data Analysis: Skilled in interpreting and analyzing complex statistical data to inform business decisions, with the ability to identify relevant trends and patterns. • Algorithm Evaluation and Optimization: Experienced in evaluating the performance of Machine Learning algorithms using relevant metrics, with a strong understanding of optimization techniques to improve model performance. • Effective Communication of Results: Adept at clearly articulating the results of Machine Learning initiatives, providing actionable insights and recommendations to drive business outcomes. • Strategic Decision-Making: Proven ability to collaborate with stakeholders to integrate Machine Learning insights into business decision-making processes, driving informed strategic choices. • Advanced Statistical Modeling: Experience with developing and applying advanced statistical models to drive business insights, leveraging techniques such as regression analysis, time series forecasting, and hypothesis testing. • Machine Learning Frameworks: Familiarity with popular Machine Learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn, with the ability to design and implement scalable Machine Learning solutions. • Data Visualization Tools: Exposure to data visualization tools such as Tableau, Power BI, or D3.js, with the ability to effectively communicate complex data insights to stakeholders. United States Infrastructure & Technology Hybrid Professional Multiple Cities (0147) International Business Machines Corporation