Senior Data Scientist

We're Hiring: Senior Data Scientist!

We are seeking to hire a Senior Data Scientist in South San Francisco, CA.

Location: South San Francisco, United States

Work Mode: Work From Office

Role: Senior Data Scientist

Pay Scale: $160, 000 - $180, 000 (Dependent on Experience)

What You'll Do

• 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

What We're Looking For

• 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

Ready to make an impact? Apply now and let's innovate together!