Senior Data Scientist

Epia Neuro•Alameda, CA

5d•Onsite

About The Position

Epia Neuro is a neural technology company developing intent-driven systems to restore function and independence for people living with neurological conditions. Its platform combines implantable neural interfaces, adaptive algorithms, and assistive devices. The company initially focuses on stroke-related motor impairment, with planned expansion into cognitive decline and other neurological disorders. The Senior Data Scientist will turn neural and behavioral data from preclinical and early human research studies into rigorous analyses and findings. The work includes characterizing signal quality and decoding performance, exploring which movements and behaviors can be extracted and decoded, and building reliable analysis workflows as data grows. This is a hands-on individual-contributor role on the Research team, reporting to the Director of Research. The role works closely with study scientists and the Software team, and contributes to study design, decoding approaches, and publications. The position is based at the company's Alameda headquarters in the San Francisco Bay Area, with an expectation to work onsite at least three days per week.

Requirements

PhD in neuroscience, neural engineering, biomedical engineering, electrical engineering, computer science, or a related quantitative field; alternatively, a Master's degree in one of these fields with 4+ years of relevant experience in a research-focused role.
Substantial hands-on experience analyzing continuous neural time-series data, ideally field potentials such as ECoG, sEEG, LFP, or EEG.
Strong foundation in neural signal processing, including filtering, spectral analysis such as band power and time-frequency methods, artifact handling, and feature extraction.
Applied machine learning experience with supervised and unsupervised methods, particularly involving noisy biological data.
Ability to independently frame scientific questions, select and defend appropriate methods, and carry analyses through to clear conclusions and actionable recommendations.
Experience aligning neural recordings with behavioral and task data.
Strong Python and scientific computing skills.
Track record of writing reusable, maintainable analysis code and using version control and sound data management practices.
Clear written and verbal communication skills and comfort working across scientific and engineering teams.

Nice To Haves

Experience with human intracranial recordings.
Experience with motor decoding, cognitive-state decoding, or closed-loop BCI.
Experience with video-based pose estimation or kinematic analysis.
Experience building data pipelines or standards shared across studies.
Experience with cloud-based data processing.

Responsibilities

Own research-study analyses end to end, from analysis strategy and statistical design through figures, readouts, and publications.
Characterize and validate in vivo neural-interface recording performance, including signal quality, noise, artifacts, and stability.
Establish preprocessing and quality-control practices for downstream analyses.
Develop and evaluate models that decode behavior from neural activity, including models used in closed-loop study sessions.
Explore neural and behavioral data, including pose estimation and kinematics, to identify new variables and research questions.
Build reproducible analysis pipelines and help define data standards across studies.
Work with study scientists to shape analysis plans and study design.
Communicate findings to scientists, engineers, and leadership.
Partner with the Software team to hand off research-grade methods and code.