Computational Scientist - Modelling & Inference

Senior Computational Scientist – Statistical Genomics & InferenceNew York, NY · Onsite · Full-TimeThe CompanyOur client is an early-stage, venture-backed genomics company in the healthcare space. They turn sequencing data into answers people can act on. The product is in commercial use, the team is small and highly technical, and the science sits at the center of the business.The OpportunityThis is the lead computational seat. You’ll own the statistical modelling and inference engine behind the product and set technical direction from day one. AI-assisted coding tools are part of how the team works. For a strong performer, the role grows into leading the computational function and building a team.What You’ll DoDevelop and apply phylogenetic and phylodynamic models (time-scaled trees, coalescent and birth–death frameworks, ancestral state reconstruction) for microbial genomic dataBuild probabilistic methods that infer relationships between samples when data is sparse or incompleteLead strain-level analysis of complex, mixed microbial samplesOwn and harden the bioinformatics pipelines, from QC through comparative genomicsMature the AWS environment (infrastructure-as-code, CI/CD, cost control) and support healthcare data-security standardsTurn model outputs into clear, interactive reportingPublish your methods with the company’s academic and public-sector collaboratorsWhat You BringPhD in population genetics, molecular evolution, biostatistics, computational biology, or a related quantitative fieldDeep grounding in likelihood and Bayesian inference, MCMC, continuous-time Markov models, coalescent/birth–death processes, and model selectionHands-on experience with BEAST, IQ-TREE, or equivalent phylogenetics toolsMachine learning fluency, including simulation-based inference; graph/network models a plusProduction AWS, Linux, and Git; Nextflow and Terraform preferredExperience using agentic/AI coding tools, and the judgment to critically review their outputMust be authorized to work in the US without sponsorship.