Senior Applied Mathematics Engineer

We are seeking a highly skilled and intellectually driven scientist or engineer with a strong foundation in mathematical modeling, simulation, and data analysis. This role bridges rigorous quantitative methods with practical product development, supporting predictive modeling, experimental design, and data-driven decision making across the full IDEXX product lifecycle - from new product development through long-term product support.

• Develop and apply mathematical models and simulations to support product design, performance prediction, and requirements development - bringing a strategic mindset to translate complex technical problems into scalable solutions.

• Build and maintain predictive models and forecasting frameworks to inform product strategy and lifecycle decisions, demonstrating decision quality and the ability to manage complexity in ambiguous, data-rich environments.

• Design and oversee/execute experiments, applying statistical and computational methods to extract actionable insights from large-scale datasets - driving results with rigor and resourcefulness.

• Translate raw data into meaningful information that shapes product and business decisions, exhibiting a strong customer focus and the ability to persuade diverse audiences through clear, evidence-based storytelling.

• Contribute to product requirements development by connecting quantitative analysis to customer and organizational needs, exercising organizational savvy and a global perspective.

• Partner with cross-functional teams across engineering, science, and commercial functions, fostering a culture that collaborates, drives engagement, and values differences.

• Apply familiarity with LLMs and AI agents to accelerate analysis workflows and identify opportunities for intelligent automation, embodying nimble learning and situational adaptability as the technology landscape evolves.

• Maintain clear, well-organized documentation of models, methodologies, and results, ensuring accountability and supporting long-term knowledge continuity.

• Bachelor's with 5 years experience, Master's with 3 years experience, or PhD with 2 years experience in Physics, Physical Chemistry, Analytical Chemistry, Chemistry, Chemical Engineering, Applied Engineering, Applied Mathematics, or a related discipline

• Proficiency in one or more of the following is required: Python, JMP, Mathematica, R, or SAS.

• Hands-on experience with robotics, instrumentation design, or hardware/software integration - from concept through implementation - is preferred, particularly where such systems were developed or adapted to support analytical or diagnostic workflows.

• Experience with big data platforms such as Snowflake or Amazon S3 is desired.

• Familiarity with LLMs and AI agent frameworks as applied to scientific or analytical workflows is desired.

• The courage to challenge assumptions, advocate for data-driven conclusions, and engage constructively across all levels of the organization.

• Demonstrated ability to manage ambiguity - comfortable operating in evolving problem spaces where requirements and priorities shift.

• Strong verbal, written, and interpersonal communication skills, with the ability to present complex findings to both technical and non-technical audiences.