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

In this role, the candidate will work with our electric utilities clients in the US to understand their grid modernization goals and help achieve them. Specifically in areas of Transmission and Distribution, Energy Management Systems (EMS), SCADA, Distribution Management Systems (DMS), Distributed Energy Management Systems (DERMS), Smart Meters (AMI), and Geographic Information Systems (GIS). It will involve understanding utility processes in the context of implementing these technologies and platforms and performing Data work and analytics.

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 Advanced Analytics Solutions: Develop and implement mathematical optimization, discrete-event simulation, and rules programming approaches to address complex business challenges. This involves preparing data, performing statistical analysis, and deploying results.
• Build Predictive Models: Utilize predictive analytics tools like SPSS to analyze data, identify patterns, and draw meaningful conclusions that inform business decisions.
• Manage Data Engineering Projects: Oversee the preparation, collection, and mining of data to ensure seamless solution delivery and effective insights generation.
• Deploy Analysis Results: Present findings and recommendations to stakeholders, ensuring that insights are actionable and drive business value.
• Apply Data Engineering Principles: Ensure that all solutions adhere to data engineering principles, enabling efficient and scalable advanced analytics projects.
  
  

This role can be performed from anywhere in the US.

Preferred Education

None

Required Technical And Professional Expertise

• Mathematical Optimization Expertise: Experience with mathematical optimization techniques, including developing and implementing approaches to address complex business challenges, and applying data engineering principles to ensure efficient and scalable solutions.
• Predictive Analytics Tools: Experience working with predictive analytics tools like SPSS to analyze data, identify patterns, and draw meaningful conclusions that inform business decisions.
• Data Engineering Principles: Experience in designing, building, and managing solutions that involve preparing data, performing statistical analysis, and deploying analysis results, with a strong understanding of data engineering principles.
• Statistical Analysis and Modeling: Experience with statistical analysis and modeling techniques, including data mining and text mining, to drive business insights and inform decision-making.
• Solution Delivery and Management: Experience in managing data engineering projects, overseeing the preparation, collection, and mining of data to ensure seamless solution delivery and effective insights generation.
  
  

Preferred Technical And Professional Experience

• Utilities - electric operations and asset management experience is a plus - either as a utility employee or in a consulting services capacity.
  
  

Discrete-Event Simulation Expertise: Experience with discrete-event simulation techniques, including developing and implementing approaches to address complex business challenges. Ability to apply data engineering principles to ensure efficient and scalable solutions.

• Rules Programming Knowledge: Exposure to rules programming approaches, including designing and implementing solutions that involve preparing data and performing statistical analysis.
• Text Mining Techniques: Experience with text mining techniques, including data mining and statistical analysis to drive business insights and inform decision-making.