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Data Scientist - Biomedical Signal ProcessingSphere Software • New York, New York, United States
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Data Scientist - Biomedical Signal Processing

Sphere Software
  • US
    New York, New York, United States
  • US
    New York, New York, United States
Postuler Maintenant

À propos

Position: Data Scientist / Machine Learning Engineer Client: AI-Driven HealthTech / Biosignal Analytics Product Engagement Type: Consulting → Potential Phase 3 Implementation Location: Remote
Role Overview We are looking for a Data Scientist / ML Engineer with a biomedical signal processing background to support development of real-time AI solutions based on physiological signals .
The role begins with consulting , followed by hands‑on model training and optimization during Phase 3 of product development .
The ideal candidate has experience working with messy physiological datasets , including ECG, EEG, EOG, brain waves, or other low‑frequency biosignals , and is comfortable building end‑to‑end ML pipelines — from signal filtering and feature engineering to real‑time model deployment .
Key Responsibilities Phase 1–2: Consulting & Architecture
Analyze physiological signal datasets and data quality
Recommend signal preprocessing and filtering strategies
Define feature engineering approach for biosignals
Suggest model architecture for real‑time predictions
Advise on data pipeline and training strategy
Help define evaluation metrics and validation approach
Phase 3: Model Training & Implementation
Process low‑frequency physiological signals (ECG, EEG, brain waves, biosignals)
Apply signal filtering, noise reduction, and transformations
Build feature extraction pipelines from physiological data
Train and optimize machine learning models
Support real‑time inference and model performance optimization
Work closely with engineering team for model integration
Improve model accuracy through experimentation and iteration
Required Experience
2+ years experience as Data Scientist / ML Engineer / Biomedical Data Scientist
Strong signal processing background
Experience working with physiological or biomedical signals such as:
ECG
EEG
EOG
Brain waves
Other biosignals
Experience working with low‑frequency signals
Experience handling noisy or heterogeneous physiological datasets
Hands‑on experience with:
Signal filtering
Mathematical filters
Feature extraction
Time‑series analysis
Python skills:
NumPy
SciPy
Pandas
Scikit‑learn
Nice to Have
Biomedical engineering background
Neuroimaging or electrophysiology experience
Experience working with multi‑source physiological datasets
Experience building reproducible research pipelines
Experience with real‑time ML solutions
PyTorch / TensorFlow experience
Engagement Model
Phase 1–2: Consulting / Advisory
Phase 3: Model Training & Implementation
Real‑time biosignal AI product
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  • New York, New York, United States

Compétences linguistiques

  • English
Avis aux utilisateurs

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