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ABOUT

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Samuel Thorpe

Born and raised in California, I received my PhD in Mathematical Behavioral Science from the University of California at Irvine. My research there centered around analyzing EEG data from healthy adults as they performed cognitive tasks, particularly attention tasks. I then completed a post doc at the University of Maryland Child Development Lab where I worked with everything from infant and monkey EEG to structural and functional MRI, studying the development of the brain. After realizing I wanted the geographic freedom to return to California, I decided to move from academia to the private sector and completed The Data Incubator Program, which helped me launch my career in data science. 

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My first role at NovaSignal allowed me to grow from Data Scientist to Principal Data Scientist as I led ML modeling projects for ischemic stroke and cerebrovascular event prediction using Transcranial Doppler (TCD). I partnered with clinical teams to integrate models in real-time diagnostic platforms and designed signal processing tools for modeling emboli detection and blood flow dynamics. 

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I've been lucky enough to continue growing as a manager and project lead at Koneksa, 

where I led design of AWS-based micro service infrastructure for FDA-regulated clinical trials, built scalable ETL pipelines integrating biosensor and PRO data across 30+ studies. At Koneksa I discovered a passion for managing a team and mentoring other engineers and scientists. 

 

There is nothing I love more than working with a room full of brilliant people, but I am also just enough of an introvert to want to close my office door and obsessively develop a project from end to end. Mainly, I am indefatigably curious. I find the world to be a profoundly interesting place to be. 

SKILLS

Programming & Platforms

Mastery of Python (expert) and

Matlab (>10 yrs) for knowledge

discovery and visualization,

together with Git, Docker, and

Linux/Bash tools for dev and

deployment.

Data Infrastructure

AWS — S3, EC2, Lambda, Athena,

CI/CD, data lakes & observability

— CloudWatch, New Relic

Extensive Applied ML

Classification, cross-validation,

GLMs, clustering, bootstrapping;

Scikit-learn, TensorFlow, PyTorch

Excellent Signal Processing

Fourier analysis, wavelets, SVD,

ICA, EMD, digital filtering

Engaging Communicator

Strong communicator across

teams and audiences; experienced

in grant writing, technical

documentation, and scientific

publishing

Dynamic Systems

Experience

Numerical ODE, nonlinear systems,

manifold learning, graph theory

 

RESUME

CONTACT 

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