Reporting Data Scientist - Project Controls
Fluor Corp.
Sacramento, CA, US
Onsite
2026-06-30
Announced salary
$96,500 - $179,500
Low
$85K
Median
$112K
High
$148K
Market in Sacramento · BLS OEWS 2025
Estimated net pay
$6,006 - $10,132
/month · 25% withheld
after tax & contributions · Single, no dependents
Job description
At Fluor, we are proud to design and build projects and careers. We are committed to fostering a welcoming and collaborative work environment that encourages big\-picture thinking, brings out the best in our employees, and helps us develop innovative solutions that contribute to building a better world together. If this sounds like a culture you would like to work in, you’re invited to apply for this role.
Fluor is seeking candidates for opportunities within our Program Delivery Support (PDS) team, working alongside the California High\-Speed Rail Authority, to provide program delivery and program management services for one of the largest planned infrastructure projects in the U.S. The system will connect the 500\-mile stretch between the Los Angeles region with the San Francisco Bay Area, with up to 24 stations. The first phase of the program is currently under construction in California’s Central Valley.
**Job Description**
-------------------
Under the general direction of the Director of Project Controls, the Data Scientist supports enterprise‑level decision‑making by developing advanced analytics, predictive models, and automated reporting solutions. This position transforms complex program, project, and operational data into meaningful insights, enabling leadership, project teams, and stakeholders to make accurate, timely, and data‑driven decisions.
The Data Scientist collaborates across functional areas—including cost, schedule, risk, and finance—to integrate data sources, improve data quality, enhance reporting workflows, and design visualization tools (e.g., Power BI dashboards) that communicate performance, trends, and risks clearly and effectively.
**Position Responsibilities**
* Develop, maintain, and continuously improve program‑wide data models, analytics frameworks, and reporting workflows.
* Build predictive and statistical models to forecast cost, schedule, risks, and performance metrics.
* Create automated dashboards, visualizatio