Industrial Data Scientist - Predictive Analytics & ML

Quanta Services, Inc.; Englewood (CO); On-site; USD 145,000 - 165,000; Full time

Benefits offered by this job

100% employer-paid health care

Employer-paid basic life insurance

Employer-paid disability benefits

401(k) with matching

Paid Time Off

Paid Holidays

Tuition Assistance

Wellness & Mental Health Programs

Learning and Development Programs

Job summary

PAR Electric Contractors, LLC is seeking a data scientist to own design and execution of predictive, optimization, and machine learning models for large-scale utility contracting. You will build data products solving operational, financial, and engineering challenges, with up to 10% travel.

The role requires strong Python/SQL skills and experience deploying models in production within asset-heavy industries. Competitive compensation and comprehensive benefits are offered.

Qualifications

• Master’s degree + 4–6 years of experience, OR a Bachelor’s degree + 6+ years of experience.
• Preferred certifications: Databricks Certified Machine Learning Professional, CAP, or AWS ML Specialty.
• Strong Python and SQL skills, with experience building predictive models that ran in production.
• Experience in construction, industrial operations, or asset-heavy, project-based industries preferred.
• Familiarity with project financial or job-costing systems (EcoSys, JDE) or cloud data platforms such as Databricks preferred.
• Experience as an early or first data science hire, building an analytics function rather than joining an established one, preferred.
• Background in geophysics, subsurface or terrain risk modeling, or geospatial analysis preferred.

Responsibilities

• Design, build, and optimize core cloud-based data pipelines and ETL processes tailored for utility infrastructure analytics.
• Partner with project managers and operations teams to identify efficiency gaps and deliver data-driven solutions.
• Work independently from a loosely defined business question through to a finished analysis or model, without an existing team to lean on.
• Build and validate models on real operational and financial data, including incomplete or inconsistently recorded data.
• Validate models against real project outcomes over time, beyond backtesting on a static dataset.
• Communicate results and their limits clearly to non-technical stakeholders in operations, finance, and leadership.
• Design and implement complex machine learning, industrial optimization, and forecasting models.
• Establish best practices for code quality, model validation, and deployment.
• Interface with executive stakeholders to present findings and align data science with operational strategies.
• Collaborate with multi-disciplinary teams to document data pipelines and workflows.
• Design intuitive charts, dashboards, and reports that highlight trends, risks, and actionable insights.
• Break down complex industrial and logistical problems into data-driven components.
• Prioritize multiple data requests and model iterations across sites or project phases.
• Follow strict scientific and statistical protocols to ensure models are reliable, reproducible, and compliant with engineering standards.
• Work across departments such as field operations, procurement, and design engineering.

Skills

Python

SQL

Machine learning

Data pipelines

Model deployment

Problem solving

Independent work

Geospatial analysis

Education

Master’s degree

Bachelor’s degree

Tools

Databricks

EcoSys

JDE

Job description

PAR Electric Contractors, LLC is seeking a data scientist to own design and execution of predictive, optimization, and machine learning models for large-scale utility contracting. You will build data products solving operational, financial, and engineering challenges, with up to 10% travel.

The role requires strong Python/SQL skills and experience deploying models in production within asset-heavy industries. Competitive compensation and comprehensive benefits are offered.