We are seeking an experienced Senior Data Scientist with a strong background in metagenomics, biostatistics, and computational biology to join our growing team. 

The successful candidate will play a key role in supporting clinical trials and other studies. They will provide critical analytical support across both translational biology and preclinical teams, while also contributing to the development of innovative statistical methods to support the company’s informatics platform.

Key Responsibilities:

Perform microbiome and multi-omics data analysis (metagenomics, transcriptomics, etc.) in conjunction with clinical metadata, particularly from our clinical trials.
Identify, develop, and implement advanced statistical, analytical, and machine learning methods to enhance our informatics platform.
Provide statistical expertise for study design, including the development of analysis plans for complex clinical datasets.
Collaborate with cross-functional teams to deliver statistical and analytical support across various projects, from preclinical studies to translational research.
Drive innovation in the application of data science techniques in drug discovery, with a focus on live bacterial therapeutics.Requirements:

Advanced degree (PhD preferred) in Data Science, Biostatistics, Computational Biology, or related field.
Proven experience in analyzing large-scale biological datasets, particularly metagenomics.
Expertise in developing and applying statistical methods in the context of clinical research.
Strong programming skills in Python, R, or equivalent languages used for data science.
Experience in working within cross-functional teams, with excellent communication and problem-solving skills.
Familiarity with oncology, immunology, or related therapeutic areas is a plus.Opportunity: This is a unique opportunity for an innovative and driven individual to influence the early development of cutting-edge technology. As part of our dynamic and multidisciplinary team, you will help shape the future of drug discovery by applying advanced data science methodologies in a fast-evolving field