Data Science & Signal Processing Intern 

Location: Hybrid – Greater Boston Area 
Duration: 4-6 Month Internship 
Compensation: Paid Internship ($30–$50/hour depending on experience) 
Potential for Full-Time Employment Following Internship 

About CranioSense 

CranioSense is an early-stage medical device company developing novel, non-invasive technology to assess elevated intracranial pressure and neurological health. Our platform combines advanced sensing technologies, physiological waveform analysis, and machine learning to generate clinically meaningful insights that can improve patient care. Backed by venture capital, grant funding, and strategic research collaborations, CranioSense operates at the intersection of medtech, data science, and biomedical innovation. 

Position Overview 

CranioSense is seeking a highly motivated Bachelor’s or Master's-level Data Science & Signal Processing Intern to support preparation and transformation of complex physiological waveform and sensor datasets. The ideal candidate will be hands-on with raw data preparation and quality inspection, writing basic data conditioning and analysis code, investigating signal quality, and converting raw photoplethysmography (PPG) waveforms into candidate features for use by CranioSense's senior data science and algorithm team. 
 
The intern will work closely with CranioSense's VP of Data Science and other technical leads, providing the data preparation, signal-processing, coding, and feature-engineering foundation needed for downstream model development and validation. Support light literature review alongside data preparation work, surfacing relevant papers on optical-based signal processing, biomedical feature engineering, and physiological modeling to build familiarity with the research context informing the senior team’s development. This is a hands-on, collaborative role with meaningful ownership of analytical workflows and outputs. 
 
This internship offers strong potential for conversion into a full-time role following successful completion. 

Key Responsibilities 

  • Prepare, organize, assess and quality-check physiological waveform (and other relevant bio-signals), sensor, clinical, and metadata datasets 

  • Develop preprocessing and signal-conditioning code to filter, normalize, segment, synchronize, and prepare raw physiological data streams 

  • Explore and mine multi-site PPG and related physiological signals to identify patterns, artifacts, data-quality issues, and candidate features 

  • Transform raw PPG waveforms into reproducible features and structured datasets for use by senior data scientists in model development and validation 

  • Write reusable Python/Matlab code and scripts to automate data preparation, feature extraction, visualization, and exploratory analysis 

  • Support dataset assembly, labeling, documentation, versioning, and traceability across clinical and development activities 

  • Perform exploratory analyses and visualizations to characterize feature behavior, cohort differences, and signal quality 

  • Collaborate with the VP of Data Science, product, engineering, and clinical teams to troubleshoot data and signal-processing issues 

  • Document methods and findings clearly for the broader data science team 

Preferred Qualifications 

  • Pursuing or recently completed a Bachelor’s or Master's degree in Biomedical Engineering, Electrical Engineering, Computer Science, Data Science, Applied Mathematics, Physics, Computational Biology, or a related quantitative discipline 

  • Strong Python/Matlab skills and experience working with scientific, engineering, biomedical, or time-series datasets 

  • Experience with basic signal processing, feature extraction, data quality assessment, preprocessing, and exploratory analysis of noisy real-world data 

  • Experience with physiological waveforms, PPG, biophotonics, optical sensing, or other biomedical sensor data preferred (ECG, ABP etc.) 

  • Comfort with NumPy, pandas, SciPy, scikit-learn, visualization tools, and related scientific-computing libraries 

  • Experience with Git, reproducible analysis workflows, and cloud-based computing environments preferred 

  • Experience with structured datasets, SQL, or modern data tooling preferred 

  • Strong attention to detail and ability to investigate complex datasets, debug analytical pipelines, and follow problems through to resolution 

  • Strong analytical, critical-thinking, and problem-solving skills with a willingness to dig into data and iterate 

  • Excellent written and verbal communication skills 

Why Join CranioSense? 

  • Work on cutting-edge biomedical technology with real clinical impact 

  • Work directly with experienced data science, product, and engineering leaders on clinically meaningful biomedical datasets 

  • Gain hands-on experience taking raw physiological signals through preprocessing and feature engineering for downstream algorithm development 

  • Operate in a fast-moving, innovation-driven startup environment 

  • Opportunity for long-term employment following internship completion 

MLSC Internship Program 

Preference may be given to candidates registered through the Massachusetts Life Sciences Center (MLSC) Data Science Internship Program. 

Apply Now