Data Engineer-Machine Learning

Introduction

A career in IBM Consulting is grounded in long-term client partnerships and worldwide collaboration. You’ll work with top companies across industries, supporting their hybrid cloud and AI transformation initiatives. Backed by strategic partners, the strength of IBM technology, and Red Hat, you’ll have the resources to create meaningful change and help clients accelerate impact. At IBM Consulting, curiosity is central to success. You’ll be supported in questioning the status quo, testing new ideas, and building innovative solutions that deliver tangible outcomes. Our growth- and empathy-driven culture supports your long-term development, while recognizing the value of your individual skills and experiences.

Your Role And Responsibilities

As a Data Engineer specializing in Machine Learning, you will use Machine Learning concepts and techniques to tackle business challenges. You will apply your expertise to support and drive informed decision-making throughout the organization.

Your Primary Responsibilities Will Include

• Develop Machine Learning Solutions: Use Machine Learning concepts and techniques to solve business challenges by interpreting statistical data and identifying relevant features to guide solution development.
• Evaluate Algorithm Performance: Select suitable algorithms and assess performance using appropriate metrics, ensuring solutions align with business needs and enable informed decision-making.
• Communicate Results: Present Machine Learning initiative outcomes clearly to stakeholders, delivering actionable insights that support business decisions.
• Implement Machine Learning Techniques: Partner with stakeholders to implement Machine Learning techniques that create business value by selecting and applying the right methodologies to achieve desired outcomes.
  
  

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• Exposure to Machine Learning Concepts: Experience applying Machine Learning concepts and techniques to address business challenges, including interpreting statistical data and identifying relevant features.
• Algorithm Development Experience: Hands-on experience working with algorithms, including choosing appropriate algorithms and evaluating performance using relevant metrics.
• Data Analysis Skills: Ability to interpret statistical data and identify relevant features to support 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 findings to stakeholders, translating them into actionable insights for business decision-making.
  
  

Preferred Technical And Professional Experience

• Advanced Algorithm Development: Experience working with complex algorithms, including evaluating performance using relevant metrics and fine-tuning for optimal results.
• Data Visualization Techniques: Exposure to data visualization tools and techniques to effectively communicate Machine Learning results to stakeholders.
• Specialized Machine Learning Tools: Familiarity with specialized Machine Learning tools and technologies, including those commonly used for natural language processing or computer vision.