Software Engineer - Analytics

Beacon Biosignals•Boston, MA

11d•$150,000 - $170,000•Remote

About The Position

Beacon Biosignals is on a mission to revolutionize precision medicine for the brain. We are the leading at-home EEG platform supporting clinical development of novel therapeutics for neurological, psychiatric, and sleep disorders. Our FDA 510(k)-cleared Waveband EEG headband and AI algorithms enable quantitative biomarker discovery and implementation. Beacon’s Clinico-EEG database contains EEG data from nearly 100,000 patients, and our cloud-native analytics platform powers large-scale RWD/RWE retrospective and predictive studies. Beacon Biosignals is changing the way that patients are treated for any disorder that affects brain physiology. Beacon Biosignals is seeking a talented software engineer to scale up our scientific outputs, which power novel clinical diagnostics and enable therapy development to improve brain health. As part of the Analytics Suites Team, you'll build and maintain scientific software tooling and automated analytics pipelines that process raw biosignal data and machine learning outputs, generate biosignal-derived metrics, and combine them with clinical metadata to render scientific outputs. You will own a wide swath of the analytics stack, from library-level tools to platform-hosted services and versioned data models, CI/CD pipelines, and customer-facing reports and dashboards. This is a product-oriented role - you'll work with clinicians and cross-functional stakeholders to identify high-impact improvements to our analytics platform. You'll also collaborate closely with neuroscientists, data scientists, and other engineering teams to develop composable, reliable tooling that powers both productized analytics and custom scientific endeavors. Why this role? You'll combine rigorous software development practices and a strong understanding of scientific analysis and experimentation to strengthen our analytics platform and deliver reproducible scientific insights at scale. At Beacon, we've found that cultural and scientific impact is driven most by those who lead by example. As such, we're always seeking out new contributors whose work demonstrates innate curiosity, a bias toward simplicity, an eye for composability, a self-service mindset, and most of all, a deep empathy toward colleagues, stakeholders, users, and patients. We believe a diverse team builds more robust systems and achieves higher impact. Beacon's robust asynchronous work practices ensure a first-class remote work experience, and we also have in-person office hubs located in Boston, New York City, and Paris.

Requirements

Extensive practical experience developing production-level software for scientific or analytics applications, monitoring their performance, and maintaining them over time
Proficiency in Python, Julia, or another scientific/data-oriented programming language
An approach to software development that emphasizes composability, efficiency, and maintainability
A rigorous approach to documentation and automated testing
A collaborative mindset - you're excited to work closely with multiple teams to achieve Beacon's analytics product goals
Strong asynchronous communication skills and a knack for making the most of synchronous collaboration

Nice To Haves

A background in a relevant scientific or computational field (e.g., neuroscience, statistics, machine learning, clinical trials) is preferred but not required - we welcome candidates who are eager to learn!

Responsibilities

Develop, deploy and monitor feature computation and analytics services that transform raw biosignal data, machine learning outputs, and clinical metadata to generate meaningful scientific results
Build high-quality composable tooling that enables data scientists to deliver scientific results at scale
Transform custom or semi-standardized data workflows into reusable tools and automated products that power clinical diagnostics and trials
Design, implement, and maintain versioned data models and transformations that enrich biosignal metrics with clinical context
Contribute to reusable, scalable customer-facing analytics products, such as automated scientific reports, dashboards and purpose-specific dataset views
Collaborate closely with teams of engineers, data scientists, and neuroscientists to understand workflow pain-points and inefficiencies that can be resolved with tooling and processes improvements
Partner with scientists, product managers, and stakeholders to identify high-impact analytics improvements that accelerate development of novel therapies and diagnostic tools