Why Complementary?
We bring rigor, agility, and deep interdisciplinary experience. Our clients value our transparency, creativity, and the peace of mind that comes from working with scientists who’ve been in the trenches.
Our philosophy
Inspired by set theory if we define a subset A, then AC represents the complement, the missing piece of the whole set.
We exist to be the expert element that completes your mission.
Whether you're building a new tool, analyzing complex data, or scaling a biotech process, we design the scientific and technical solution that fits you, no boilerplate, no assumptions.
Co-founder & Data Architect
Arthur is the person you call when the data is scattered, the system’s a mess, and nobody knows where the pipelines are breaking. With a PhD in evolutionary biology (fueled by a love of craft beer and microbial systems), he’s worked across biotech, chemistry, agriculture, and bioinformatics, supporting everything from brewer's yeast to blueberries and sugarcane.
He brings hands-on experience in both upstream and downstream process development, and since 2021, he’s been helping startups modernize, digitize, and actually make use of their data. At Complementary Analytics, he leads data architecture and cloud integrations, building the digital infrastructure that lets teams move faster and scale smarter.
Arthur’s superpower is his "I can fix it" mindset, paired with great people skills and a deep understanding of how science gets done. Whether he’s wrangling cloud platforms or mentoring scientists in R, he brings calm confidence, good humor, and a “no problem too big” attitude to every challenge.
Co-Founder & Statistical Lead
Javi is a scientist who sees beauty in complexity and power in clarity. With a strong foundation in ecology, microbiology, and statistical theory, she builds models and tools that help teams ask better questions. At Complementary Analytics, she leads statistical modeling and user interface development, designing products that make data not just accessible, but inviting.
With over a decade of experience in R (and a growing love for Python), Javi has worked on everything from modeling anthrax outbreaks and animal movement to seed dispersal dynamics with sparse, noisy data. She’s also trained scientists in pharma and academia to understand, trust, and explore their data with confidence.
Javi is passionate about making science usable, where tools should be intuitive, insights actionable, and even complex models grounded in real-world impact. She’s known for her obsession with reproducibility, and her drive to empower teams through thoughtful, well-communicated analysis. Javi brings curiosity, precision, and a deep belief in science as a force for good.