Hi! I'm a computational neuroscientist pivoting fully out of the wet lab into data engineering. My background is in systems neuroscience, building MATLAB codebases to analyze and quantify preclinical biomarkers in animal models.
Recent project is a containerized biosignal pipeline to analyze human EEG data:
* Uses Prefect/Python for orchestration and ingesting
* DuckDB or Snowflake for storing cleaned raw data
* dbt for modeling sleep architecture, average band power, and other metrics
* Pandera for enforcing data contracts, rejecting corrupt signal data before warehouse loading
* CI with Pytest/GitHub Actions
I'm looking for a full-time position within data engineering. I'm particularly interested/strong in high-frequency time-series data analysis (e-phys, biosignals, energy grids, etc.). I'm a quick learner and am really eager to pick up additional stacks and technologies.
Hi! I'm a computational scientist pivoting fully out of the wet lab into data engineering. My background is in systems neuroscience, building MATLAB codebases to analyze and quantify preclinical biomarkers in animal models.
Recent work:
• Cloud-native analytics pipeline for human EEG data - uses Python for ingesting, Snowflake to store cleaned raw data, dbt to model sleep architecture, average band power, and overall orchestration.
• Pipeline for time-series data visualizations, done in Python, Docker, and Nextflow.
Starting Georgia Tech's OMSCS program in January to deepen CS fundamentals.
I'm looking for a full-time position within computational science or data engineering. I'm particularly interested/strong in high-frequency time-series data analysis (e-phys, biosignals, energy grids, etc.). I'm a quick learner and am really eager to pick up additional stacks and technologies.
Hi! I'm a computational scientist transitioning fully out of the wet lab into a purely software/data-focused role. My core strengths are in building/testing automated data pipelines. In my previous role, I developed a MATLAB codebase that analyzed neurophysiological data to identify multiple groups of clinical biomarkers in animal models. On my Github you can find a simplified version of this rebuilt using Python, Docker, Nextflow, and Pytest to visualize complex time-series data.
Starting Georgia Tech's OMSCS program in January to deepen CS fundamentals.
I'm looking for a full-time position within computational science, bioinformatics, QA automation/SDET, SRE, or types of Python-focused tech support/data analyst roles. I'm a quick learner and am really eager to pick up additional stacks and technologies.
Remote: Yes
Willing to relocate: No
Technologies: Python, SQL, DuckDB, Snowflake, dbt, Prefect, Docker, Pandera, GitHub Actions, biosignal processing (MNE/NumPy)
CV: https://drive.google.com/file/d/1ijwZUUQ1h7iYxMYUP-WVzHlhMZg...
Email: bc (at) blaiseclarke.com
Hi! I'm a computational neuroscientist pivoting fully out of the wet lab into data engineering. My background is in systems neuroscience, building MATLAB codebases to analyze and quantify preclinical biomarkers in animal models.
Recent project is a containerized biosignal pipeline to analyze human EEG data:
* Uses Prefect/Python for orchestration and ingesting
* DuckDB or Snowflake for storing cleaned raw data
* dbt for modeling sleep architecture, average band power, and other metrics
* Pandera for enforcing data contracts, rejecting corrupt signal data before warehouse loading
* CI with Pytest/GitHub Actions
I'm looking for a full-time position within data engineering. I'm particularly interested/strong in high-frequency time-series data analysis (e-phys, biosignals, energy grids, etc.). I'm a quick learner and am really eager to pick up additional stacks and technologies.