Computational Scientist - Modelling & Inference

Discover International; New York (NY); On-site; USD 180,000 - 280,000; Full time

Benefits offered by this job

AWS credit

Professional development

Job summary

Discover International in New York invites applications for a Senior Computational Scientist in Statistical Genomics & Inference. You will own the statistical modelling and inference engine behind the product, setting technical direction from day one and collaborating with academic and public-sector partners.

You will lead phylogenetic modelling, build probabilistic methods for sparse data, and oversee bioinformatics pipelines from QC to comparative genomics, while maturing AWS infrastructure

Qualifications

• PhD or equivalent in population genetics, biostatistics, or computational biology.
• Strong grounding in likelihood and Bayesian methods; ML fluency.
• Experience with phylogenetics tools and workflow systems.
• Ability to design inference algorithms for sparse data.

Responsibilities

• Develop and apply phylogenetic and phylodynamic models for microbial genomic data.
• Build probabilistic methods that infer relationships between samples when data is sparse or incomplete.
• Lead strain-level analysis of complex, mixed microbial samples.
• Own and harden the bioinformatics pipelines, from QC through comparative genomics.
• Mature the AWS environment (infrastructure-as-code, CI/CD, cost control) and support healthcare data-security standards.
• Turn model outputs into clear, interactive reporting.
• Publish your methods with the company’s academic and public-sector collaborators.

Skills

Bayesian inference

Likelihood inference

Machine learning

MCMC methods

Population genetics

Education

PhD in population genetics / computational biology

Tools

BEAST

IQ-TREE

Nextflow

Terraform

AWS

Linux

Git

Job description

Senior Computational Scientist – Statistical Genomics & Inference

The Company

Our 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 Opportunity

This 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 Do

• Develop and apply phylogenetic and phylodynamic models (time-scaled trees, coalescent and birth-death frameworks, ancestral state reconstruction) for microbial genomic data
• Build probabilistic methods that infer relationships between samples when data is sparse or incomplete
• Lead strain-level analysis of complex, mixed microbial samples
• Own and harden the bioinformatics pipelines, from QC through comparative genomics
• Mature the AWS environment (infrastructure-as-code, CI/CD, cost control) and support healthcare data-security standards
• Turn model outputs into clear, interactive reporting
• Publish your methods with the company’s academic and public-sector collaborators

What You Bring

• PhD in population genetics, molecular evolution, biostatistics, computational biology, or a related quantitative field
• Deep grounding in likelihood and Bayesian inference, MCMC, continuous-time Markov models, coalescent/birth-death processes, and model selection
• Hands-on experience with BEAST, IQ-TREE, or equivalent phylogenetics tools
• Machine learning fluency, including simulation-based inference; graph/network models a plus
• Production AWS, Linux, and Git; Nextflow and Terraform preferred
• Experience using agentic/AI coding tools, and the judgment to critically review their output

Must be authorized to work in the US without sponsorship.