Senior Data Scientist
Tap Growth ai
- San Francisco, CA
- $160,000-180,000 per year
- Permanent
- Full-time
⏰ 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 strategyWhat 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 audiencesReady to make an impact? 🚀 Apply now and let's innovate together!