Scientific Software Engineer
RemoteJersey, Georgia, United States
Job Summary
Build, extend, and polish the library of fundamental models powering Virtual Jar and Decision Blue, delivering new versions in Python to optimize coagulant and chemistry decisions for water-treatment plants. Collaborate with the Digital Solutions team to refine requirements, then implement literature-grounded functional forms with calibration, validation, and honest uncertainty reporting within a Git workflow. Expand optimization coverage to adjacent processes including pre-oxidation, adsorption, filtration, and charge neutralization while partnering with subject-matter experts to integrate regulatory drivers like TOC removal and DBP rules. This delivery-focused role bridges science and software to ensure production-ready code that meets client optimization needs. Occasional travel is required (approximately 10%).
Required Qualifications
- Water-treatment domain fluency centered on coagulation and the treatment train
- coagulant behavior
- NOM/organics removal
- DBP formation
- oxidation
- filtration
- A degree in chemical, environmental, or civil engineering, or equivalent applied depth
- Strong Python engineering
- the ability to build, test, document, and ship model code in a Git workflow
- Scientific modeling discipline, including calibration, validation, parameter control, and reporting
- Exceptional communication, with the ability to hold a highly technical conversation about the subject matter with scientists, engineers, and developers alike
- Collaboration
- The judgment to flag feasibility or other concerns early
- the initiative to help scope the work needed to resolve them
- Willingness to travel occasionally (approximately 10%)
Desired Qualifications
- Applied or published experience with coagulation, NOM/organics, ozonation, adsorption, or filtration modeling
- Familiarity with statistical/ML methods as one tool alongside physically-grounded models
- Experience translating research models into deployed software
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