Senior/Staff Data Scientist at Ceribell, Inc
Sunnyvale, CA
$184,000–$200,000
Aug 4, 2026
Sunnyvale, CA
Nov 9, 2026
What this job asks for AI summary
A medical device company building point-of-care EEG technology is hiring a data scientist/algorithm engineer to design and develop classification algorithms for neurological indications. The role centers on applying machine learning, statistical signal processing, and time-series analysis to biomedical EEG data, with responsibilities spanning model development, regulatory validation, and mentoring junior team members. It suits a PhD-level researcher with deep experience in signal processing and ML who is interested in clinical applications.
Senior level · 7+ years · Doctorate required · Full-time
Pay in the description: $184,000–$200,000
“or” means any one of them counts — you don't need all of them.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Aug 5, 2026. It is a model, not a headcount.
Why we read it this way (6)
The job title is 'Data Scientist/Algorithm Engineer' — the role is heavily algorithm-development and signal-processing focused, making it a close call between Data Scientists (15-2051) and Computer Occupations, All Other (15-1299); 15-2051 was chosen as the primary because ML modeling and statistical analysis are central to the day-to-day work.
Python, MATLAB, and R are listed together as interchangeable options ('and/or … or similar'); Python is named as the primary with MATLAB and R as alternatives.
Deep learning architectures (CNNs, RNNs) and EEG experience are listed under a 'Strong preference' qualifier, placing them as preferred rather than hard gates.
A PhD is explicitly required ('PhD in Electrical Engineering, Computer Science, Statistics, or equivalent disciplines'), making it a hard degree gate.
The 7+ years figure is stated at the role level against a broad set of disciplines, not tied to any single named technology, so it is captured as the overall experience minimum.
Ignored 1 non-technology phrase(s) as skills (responsibilities/concepts, not named tools): time-series analysis.
Read the full posting
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