Data Engineer-Machine Learning
IBM
A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. Youâ€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, youâ€ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. Youâ€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 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: Apply Machine Learning concepts and techniques to address business challenges, interpreting statistical data and identifying relevant features to inform solution development.
- Evaluate Algorithm Performance: Choose appropriate algorithms and evaluate their performance using relevant metrics, ensuring that solutions meet business needs and drive informed decision-making.
- Communicate Results: Clearly communicate the results of Machine Learning initiatives to stakeholders, providing actionable insights that inform business decisions.
- Implement Machine Learning Techniques: Collaborate with stakeholders to implement Machine Learning techniques that drive business value, selecting and applying relevant methodologies to achieve desired outcomes.
Master's Degree
Required Technical And Professional Expertise
- Exposure to Machine Learning Concepts: Familiarity with applying Machine Learning concepts and techniques to address business challenges, including interpreting statistical data and identifying relevant features.
- Algorithm Development Experience: Experience working with algorithms, including choosing appropriate algorithms and evaluating their performance using relevant metrics.
- Data Analysis Skills: Ability to interpret statistical data and identify relevant features to inform solution development.
- Machine Learning Implementation: Exposure to implementing Machine Learning techniques, including collaborating with stakeholders to select and apply relevant methodologies.
- Technical Communication: Experience communicating complex technical results to stakeholders, providing actionable insights that inform business decisions.
- Advanced Algorithm Development: Experience working with complex algorithms, including evaluating their performance using relevant metrics and fine-tuning for optimal results.
- Data Visualization Techniques: Exposure to data visualization tools and techniques, enabling effective communication of Machine Learning results to stakeholders.
- Specialized Machine Learning Tools: Familiarity with specialized Machine Learning tools and technologies, such as those used for natural language processing or computer vision.