AI Data Scientist; Transcriptomics & cfRNA Alzheimer’s Disease Research

Position: AI Data Scientist (Transcriptomics & cfRNA for Alzheimer’s Disease Research)
# AI Data Scientist (Transcriptomics & cfRNA for Alzheimer’s Disease Research)
Superfluid DX, Inc.

Full Timemid South San Francisco, California, US $160k – $200k Posted 2 days ago##

Role Overview Superfluid DX, Inc. is hiring a mid-level AI Data Scientist (Transcriptomics & cfRNA for Alzheimer’s Disease Research). This is a full-time role in South San Francisco, California. Part of Superfluid DX, Inc.'s Risk hiring, posted 2 days ago. The posted range is $160k to $200k. Full responsibilities, required qualifications, and the apply link are listed in the description below.##

Salary Context

This role offers $160k-$200k. The median for Mid-level Risk roles is $84k-$101k (based on 44 listings). 94% above median.## Resume Keywords to Include Make sure these keywords appear in your resume to improve ATS scoring

PythonRAWSLinux Git Tensor Flow Py Torch CI/CDSign up free to auto-tailor your resume with all these keywords and get a higher ATS score## Job description

Role: AI Data Scientist (Transcriptomics & cfRNA for Alzheimer’s Disease Research)

Location:

On Site 249 East Grand Avenue, South San Francisco, CA 94080

Company:
Superfluid DX, Inc.### About UsSuperfluid is developing the first high-performance, predictive blood-based test for Alzheimer’s Disease (AD), related dementias and cognitive decline that directly assays mRNA transcripts from the brain via its platform technology of cell-free messenger RNA (cf-mRNA) analysis. This next-generation novel liquid biopsy technology enables non-invasive measurement of the dynamic biology of organs throughout the body, including the brain.

Our precise understanding of the underlying pathways of disease will transform AD disease care and treatment.

Superfluid has a small but mighty team including Founder Steve Quake (Stanford Professor and Head of Science at CZI) and CEO Gajus Worthington (Former Founder/CEO of Fluidigm). Superfluid has published extensively in multiple peer-reviewed journals. Superfluid is well funded by notable investors including Brook Byers and Reid Hoffman and is also supported by the NIH and Alzheimer's Drug Discovery Foundation.

Position Overview:

We are seeking a visionary AI Data Scientist to join our cell-free RNA (cf-RNA) team. This role is designed for a technical leader who can bridge the gap between advanced Generative AI/Deep Learning and the intricate biology of cf-RNA. You will drive the development of next-generation predictive and prognostic models for AD by architecting AI solutions that are fundamentally grounded in biological rigor.

The ideal candidate understands that "Garbage In, AI Out" is the primary risk in liquid biopsy. We need a scientist who can master the secondary and tertiary analysis of cf-RNA (normalization, batch correction, noise quantification) to build AI models - including, but not limited to, foundation models and Transformer-based architectures - that are robust enough for clinical-grade implementation.

This is not a remote position - this role is fully on site.

Key Responsibilities:

* AI Architecture for Genomics:
Lead the design and deployment of AI/ML frameworks optimized for high-dimensional cf-RNA sequencing data to deliver clinically actionable AD insights.
* Biological Data Engineering:
Develop sophisticated "AI-ready" data preprocessing workflows, including advanced methods for differential expression, batch effect mitigation, and normalization that preserve subtle biological signals.
* Model

Innovation: Build and fine-tune predictive models, ranging from traditional ensembles (Survival models, Random Forest, XGBoost) to Deep Learning architectures and RNA-seq Foundation Models (LLMs) for feature extraction and zero-shot inference.
* Translational Validation:
Bridge the gap between "silicon" performance and "clinical" reality by leading hypothesis-driven investigations to ensure AI outputs meet rigorous regulatory and biological standards.
* Scalable AI Pipelines:
Architect end-to-end pipelines that integrate raw NGS outputs into scalable cloud-based AI feature stores, ensuring reproducibility and data governance.
* Strategic Leadership:
Collaborate with wet-lab and clinical teams to translate complex…