Research Data Analyst

Senseye • Austin, TX

2d • Onsite

About The Position

Senseye is a NeuroTechnology Company in Austin, TX on the cusp of revolutionizing Mental Health. Over the past 6 years we have invested millions of dollars in R&D to build our platform allowing us to measure cognitive activity via the eye through mobile phones. Through multiple iterations and use cases we are now focused on building the world's first Objective Mental Health Diagnostics on top of our core technology. Our first diagnostic is for PTSD and is entering clinical trials now, followed soon by additional indications for Anxiety and Depression. As the world struggles with a mental health crisis, it is not hyperbolic to suggest that an objective diagnostic platform, that gives clinicians a safe and objective accurate approach to identifying and monitoring mental health disease, will redefine how mental health services are provided and will enable access to treatment for hundreds of millions of sufferers. The Senseye platform has the potential to be the technology that drives this change. We are seeking a Research Data Analyst to join our team. This is an analysis-first role embedded with our data science and research personnel: you will design, run, and interpret analyses of experimental data across the full lifecycle of a research study. We use AI-assisted tools to help us write analysis code faster and better, but you need a solid grasp of coding and how the code works: as the human in the loop, you have the final say on what gets released and how it is analyzed, and spotting bugs and subtle mistakes is far easier for someone who genuinely understands the code than for someone who relies entirely on AI. You will co-create hypotheses with our senior scientists, own the execution of analyses, and provide the initial interpretation of results: the experimental logic, their validity, and what they actually mean. The signals we work with are small, so every detail matters. The ideal candidate is passionate about being part of an innovative research team, detail-oriented, adaptable, and motivated to grow. You will collaborate with our Research and Data Scientists and be involved in many aspects of our work, from experiment design through analysis and reporting.

Requirements

• Bachelor's degree in Neuroscience, Psychology, Computer Science, Statistics, Data Science, or a related quantitative or bioscience field.
• Working proficiency in Python and scientific computing libraries (e.g., NumPy, Pandas, Matplotlib) for data analysis and statistical work.
• A solid understanding of the research workflow: experimental design, hypothesis formulation, execution, analysis, and interpretation of results.
• The ability to critically evaluate analysis code and outputs — catching small errors matters, because the effects we measure are small.
• Strong attention to detail and a root-cause mindset: you don't stop at “this looks wrong” — you dig in and find out why.
• Clear written communication and the ability to produce readable reports of methods and findings.
• Motivation to learn and improve. You don't need to be an expert in any one field, but you should be eager to build on your skills.
• An outside-the-box mindset: we don't need a robot — we want someone willing to take risks, try new approaches, and push an analysis beyond what an AI prompt hands back, because you care to understand what's really going on.

Nice To Haves

• Master's degree in Computer Science, Statistics, Data Science, Neuroscience, Psychology, or a related field.
• Laboratory or human subjects research experience (academic lab, thesis project, internship, or publication).
• Experience with research statistics (e.g., parametric, nonparametric, or Bayesian statistics).
• Experience using AI coding assistants effectively — prompting, reviewing, and correcting generated code.
• Experience preparing manuscripts for publication.

Responsibilities

• Plan and execute analyses of experimental data with support from our research and data science team: co-develop a clear hypothesis, specify expected outcomes, and select appropriate statistical methods before running the analysis.
• Use Python and AI-assisted coding tools to build analysis pipelines and statistical tests, critically reviewing generated code for correctness.
• Validate results end to end: check data quality, verify assumptions, spot anomalies and subtle errors, and trace unexpected results to their root cause.
• Interpret findings in the context of the experimental design, and be clear about what the results do and do not support.
• Present results of analyses to team members on an ongoing basis.
• Write clear, well-organized analysis reports documenting methods, results, and interpretation.
• Prepare, maintain, and update technical documentation.
• Attend weekly project meetings and collaborate closely with data science and research team members through study design, execution, analysis, and interpretation.
• Other duties and responsibilities may be assigned by research supervisors.

Benefits

• The freedom and trust to define your role as we design, build, and ship our products
• Competitive salary and stock option plan
• Flexible paid time off (vacation, sick leave, and public holidays)
• Flexible schedules
• Company health care plan
• Medical, dental, and vision insurance
• Short and long term disability insurance
• Life insurance policy
• 401k
• Commuter benefits for parking, public transit, carshares, etc.
• Mothers' room
• Fully stocked kitchen
• Opportunities for continuing education

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level