Data Engineer-Machine Learning

Overview

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 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.