Digital Innovation & Analytics Lead

Heidelberg Materials; Irving (TX); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Annual incentive plan

401(k) plan with company match

Competitive benefits

Job summary

Heidelberg Materials invites applications for a leadership role guiding data science initiatives across HROC services and plant performance. You will drive AI adoption, analytics projects, and collaboration with operations, engineering, and external partners to deliver measurable improvements.

Ideal candidates bring strong Python expertise, ML framework experience, and a track record of production-ready analytics in industrial settings.

Qualifications

• Lead analytics/AI initiatives from ideation to deployment.
• Strong understanding of data science lifecycles and feature engineering.
• Experience with cloud AI environments (Azure/AWS/GCP).
• Proficiency in Python and ML frameworks.
• Manufacturing or heavy industrial experience preferred.

Responsibilities

• Lead identification, prioritization, deployment, and scaling of digital solutions for HROC services.
• Drive adoption of AI, analytics, automation and digital twins.
• Provide leadership for HROC data science resources and analytics portfolio.
• Collaborate with operations, engineering, and external providers to deliver improvements.
• Manage SparkHub and run Discovery Sessions and Innovation Jams to align with priorities.
• Develop and implement innovative solutions for continuous improvement and digital transformation.

Skills

Analytics leadership

ML development

Python

Cloud AI environments

Data science lifecycle

Model evaluation

Education

Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering

Tools

Python

Scikit-learn

TensorFlow

PyTorch

LangChain

Semantic Kernel

Job description

Heidelberg Materials invites applications for a leadership role guiding data science initiatives across HROC services and plant performance. You will drive AI adoption, analytics projects, and collaboration with operations, engineering, and external partners to deliver measurable improvements.

Ideal candidates bring strong Python expertise, ML framework experience, and a track record of production-ready analytics in industrial settings.