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# Data Scientist

- **Company:** U.s. Par Electrical Contractors, Llc
- **Location:** Englewood, CO, United States
- **Experience:** Expert
- **Salary:** $145,000.0 - $165,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Bioinformatics, Software Quality, Document-Oriented Databases, Python (Programming Language), Machine Learning, Standard Sql, Model Validation, Data Analytics, Databricks
- **Published:** October 28, 2026
- **Apply:** https://www.builtincolorado.com/job/data-scientist/11928336?handler=ApplyRedirect

## About the Role

* Master's degree + 4-6 years of experience, OR a Bachelor's degree + 6+ years of relevant experience required.

 * Preferred certifications: Databricks Certified Machine Learning Professional, Certified Analytics Professional (CAP), or AWS ML Specialty.

 * Strong Python and SQL skills, with experience building predictive models that ran in production.

 * Very high attention to detail.

 * Excellent problem-solving skills.

 * Ability to work independently but as part of a team.

 * Experience in construction, industrial operations, engineering, or another asset-heavy, project-based industry preferred.

 * Familiarity with project financial or job-costing systems (EcoSys, JDE, or similar) 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., PAR Electrical Contractors, LLC does not sponsor applicants for work visas. All applicants must be legally authorized to work in the United States. PAR Electrical Contractors, LLC participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. PAR Electrical Contractors, LLC will only use E-Verify once you have accepted a job offer and completed the Form I-9.

## Description

PAR Electric is seeking a highly motivated Data Scientist to own the design and execution of complex predictive, optimization, and machine learning models. This role works independently, reporting to the Director of AI & Machine Learning, building data products that solve intricate operational, financial, and heavy industrial engineering challenges inherent to large-scale utility contracting., * 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 or pipeline to lean on.

 * Build and validate models on real operational and financial data, including data that is incomplete, unlabeled, or inconsistently recorded.

 * 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 recommendations, as well as align data science capabilities with operational strategies.

 * Collaborate with multi-disciplinary teams to document data pipelines and workflows.

 * Design intuitive charts, dashboards, and reports that clearly highlight trends, risks, and actionable operational insights.

 * Break down complex, unstructured industrial and logistical problems into logical, data-driven components.

 * Prioritize multiple data requests and model iterations across different active construction sites or project phases.

 * Follow strict scientific and statistical protocols to ensure models are reliable, reproducible, and compliant with engineering standards.

 * Work effectively across siloed departments, such as field operations, corporate procurement, and design engineering teams.

 * Ensure high-quality, clean, and mathematically sound datasets.

 * All other duties assigned by management