Senior Scientific Programmer

Summary

Datacor, including its GoldSim business, provides software solutions for process manufacturing, scientific modeling, and simulation. The Senior Scientific Programmer will own numerical solutions and algorithms for GoldSim’s simulation engine, implement them in C++, build and verify models, document methods, and collaborate with engineering, QA, product, and customer support teams. The role also contributes to modernizing computational capabilities, including potential applications of machine learning to scientific simulation.

Responsibilities

• Own the numerical solutions and mathematical/computer science algorithms underlying GoldSim's simulation engine - from the theoretical foundation (equations, algorithm design) through to implementation in our C++ codebase
• Push practical, real-world improvements to GoldSim's numerical capabilities, and propose new features driven by everyday or discipline-specific customer needs
• Participate in design discussions across the full development lifecycle, not just the mathematical layer
• Build GoldSim models that apply and exercise the platform's numerical capabilities - for QA and verification, as example models shipped with the product, and in direct support of customers
• Use hands-on model-building as a primary way to validate that new or improved algorithms behave correctly in practice
• Document both the theoretical basis (equations, algorithm descriptions) and the practical implementation of GoldSim's numerical methods, so this knowledge isn't concentrated in one person
• Partner with the founding engineer to formalize existing modeling, QA, and support methodology
• Work alongside the software engineering team to integrate new or improved numerical capabilities into the broader platform
• Translate business and product requirements into technical specifications
• Serve as a technical resource for customer support and QA on advanced modeling and numerical questions
• Communicate technical/mathematical concepts clearly to engineers, QA, and product stakeholders
• Bring curiosity for modern computational approaches - including applying machine learning to accelerate, approximate, or extend traditional numerical simulation methods
• Help identify opportunities to modernize GoldSim's existing algorithmic infrastructure

Skills

• Masters or PhD level in science or engineering, with outstanding academic performance
• Broad experience with applied math and numerical methods for solving science and engineering problems (e.g., matrix algebra, numerical methods for solving partial differential equations)
• Earth sciences or civil engineering background, preferably including contaminant transport modeling
• Extensive C++ programming experience, ideally in scientific or engineering applications; familiarity with commercial or open-source numerical libraries and frameworks is a plus
• Proven ability to design and implement practical numerical solutions to real-world problems
• Good communications skills, must write effectively and enjoy interacting with other team members
• Experience developing and supporting Windows desktop applications is a plus, as is hands-on experience with data science tools such as MATLAB, R, or Tableau
• Experience applying AI/ML techniques (e.g., machine learning models, LLM-based tools, or AI-assisted development) to scientific or engineering software is a plus

Qualifications

Must Haves

• Masters or PhD level in science or engineering, with outstanding academic performance
• Broad experience with applied math and numerical methods for solving science and engineering problems (e.g., matrix algebra, numerical methods for solving partial differential equations)
• Earth sciences or civil engineering background, preferably including contaminant transport modeling
• Extensive C++ programming experience, ideally in scientific or engineering applications; familiarity with commercial or open-source numerical libraries and frameworks is a plus
• Proven ability to design and implement practical numerical solutions to real-world problems
• Good communications skills, must write effectively and enjoy interacting with other team members

Nice to Haves

• Experience developing and supporting Windows desktop applications is a plus, as is hands-on experience with data science tools such as MATLAB, R, or Tableau
• Experience applying AI/ML techniques (e.g., machine learning models, LLM-based tools, or AI-assisted development) to scientific or engineering software is a plus

Benefits

• Flexible opportunity to work from Datacor's US offices as you would like, including the Seattle office