Senior Data Scientist – Cell-Free RNA Sequencing Read More

Responsibilities

• Lead innovation in secondary and tertiary analysis of cf-RNA sequencing data, focusing on delivering rigorous and reproducible results
• Develop and implement advanced methods for differential gene expression analysis, pathway analysis, and enrichment analysis, optimizing for accuracy and biological insights
• Build, train, test, and validate predictive models, including logistic regression, random forests, and neural networks, as well as leverage existing RNA-seq large language models (LLMs) for inference and analysis
• Design and build scalable, efficient data analysis pipelines
• Engage in hypothesis-driven research, rigorously testing and validating new methods and models
• Critically evaluate results, ensuring robust models that are applicable in real-world clinical contexts beyond academic publications
• Visualize complex datasets and create compelling narratives to communicate findings to both scientific and executive audiences
• Collaborate with cross-functional teams, contributing to the company’s overall scientific and technical strategy

Qualifications

• PhD in a quantitative field with a strong focus on biological sciences (e.g., Applied Statistics, Biophysics, Computational Biology)
• Postdoctoral experience is highly desirable
• 5+ years of biotech industry experience with a proven track record of leading successful projects
• Expertise in gene expression data analysis, including count table filtering, normalization strategies, noise quantification, differential expression analysis, and dimensionality reduction
• Strong foundation in statistical principles and rigorous application; including, but not limited to, hypothesis testing, P-value corrections, Bayesian approaches, bootstrapping, and permutation testing
• Extensive experience in building, training, testing, and validating machine learning and deep learning models, including model selection based on comparative analysis and performance metrics
• Proficient in feature set development (selection, engineering, etc.) and skilled in updating and performing inference with RNA-seq-specific large language models (LLMs)
• Ability to innovate both in applying library methods and developing algorithms from scratch
• Experience with common data science infrastructure, including pipelines, clusters, databases, and feature stores; direct experience with cloud platforms (AWS preferred) for scaling, deploying, and managing data workflows is a strong advantage
• Proficient in Python and Unix/Linux environments; additional proficiency in other languages (e.g. R, Julia, Rust) is a strong plus
• Strong coding skills across the software development lifecycle
• Deep scientific curiosity and a solid grasp of the scientific method, hypothesis testing, and model validation
• Passion for building predictive and prognostic models that perform effectively in real-world applications
• Independent research capabilities, with the ability to drive projects with minimal supervision
• Exceptional data visualization skills and the ability to translate complex datasets into actionable insights
• Excellent communication skills, with the ability to message both technical and executive-level audiences

Pay

The estimated salary range for this role is $160,000–$190,000 and is based on a number of factors including experience and qualifications.

Benefits

• Meaningful pre-IPO equity
• Comprehensive benefits package