Research Data Scientist

Research data is wild. It pours in from brain scans, genome sequencing, EEG and eye-tracking, biospecimens and wearables that track sleep and movement, across dozens of sites and years of study. Lasso Informatics ropes it in: our platform pulls it all into one place so researchers around the world can stop fighting with their data and get to discoveries faster.

That is where our name comes from. A lasso brings something wild under control, and that is the job. The people who do it are Wranglers, and we are quite choosy about who earns the title. Wranglers expect a lot of themselves, make everyone around them better, and never stop learning. We move fast, we have fun, and we keep the bar high.

What We Offer

• A flexible, hybrid or remote position
• Competitive compensation and benefits
• Work that matters, with scientific and clinical impact you can point to
• Variety that keeps it interesting: no two studies, measurements, or datasets look the same
• Room to grow with a mission-driven company at the front of research data management
• A sharp, multidisciplinary team that is good at what it does and good to work with

Full Time

Canada-based: $95,000 - $122,000 CAD

US-based: $105,000 - $135,000 USD

Want to Be a Wrangler? Here's What We Look For

• You hold yourself to a high scientific and technical standard, and you can defend your reasoning under scrutiny
• You make the people around you better
• You stay curious and keep learning
• You see a problem and start solving it, without waiting to be asked
• You think in systems: you create the tool once and let it hold up across hundreds of cases
• You document your work clearly enough that someone else could pick it up
• You communicate well with engineers, data managers, and researchers who don't share your technical background, and with collaborators who need a translator between their science and our platform
• You take data quality and responsible stewardship of research data seriously

About the Role

This is a hands-on data science role supporting our study operations function. You bring real fluency in bioinformatics and in how clinical data gets collected across multi-site research consortia, not just inside a single study in one lab. You turn this fluency into standards and support that the rest of the organization, and our collaborators, can build on.

Reporting to the Senior Director, Operational Initiatives, y ou work directly with the research teams and study sponsors we support, helping them translate their measures and data collection plans into clear, well-structured data dictionaries inside the Lasso platform. You are also the person collaborators turn to for more than data storage: because of your scientific training, you help them navigate the full suite of Lasso products and offer guidance that runs the full distance from data ingestion through analytic workflows, all customized to their specific study needs.

This kind of judgment call has to hold up across many collaborators and studies so you must be a person who can live in the trees while never losing sight of the forest (you are a strategic/systems thinker). You configure the reusable tools, structured workflows and decision frameworks that let your methodology and support run consistently and efficiently at scale. Other teams and collaborators come to you when they need your approach reproduced reliably, and you own the fidelity of that work as it grows.

What You'll Do

Collaborator Data & Measure Design

• Work directly with research teams and study sponsors to translate their measures and data collection plans into clear, well-documented data dictionaries inside the Lasso platform
• Advise collaborators on how to structure and document their data so it holds up to scientific and regulatory scrutiny
• Serve as the point of contact for collaborator questions about data structure, quality standards, and how their measures map onto the Lasso platform

Full-Service Scientific Support

• Help collaborators navigate the full suite of Lasso's products
• Help collaborators design and set up analysis workflows suited to their study
• Offer guidance that runs the full distance from data ingestion through analytic workflows, all customized to each study's specific needs, drawing on your own research training
• Apply bioinformatics expertise to how clinical and biological data get structured, quality-checked, and analyzed across large research consortia
• Work with data engineering and pipeline teams to configure collaborator-facing data standards directly into processing and analytics pipelines
• Review pipeline output against the standards you've set and correct drift when you find it

Scaling & Tooling

• Configure reusable tools, structured workflows, and decision frameworks that let your methodology and support run consistently and efficiently across collaborators and at scale
• Train other team members on the tools and standards you create, and serve as the subject-matter expert they come to with questions

Qualifications

Required

• PhD in neuroscience, psychology, bioinformatics, biostatistics, data science, or a related field plus relevant postdoctoral or applied research experience, or a master's degree in one of these fields plus 5+ years of directly relevant experience
• Direct experience with clinical or biomedical data collection inside a multi-site research consortium
• Strong bioinformatics background and hands-on experience with biological or clinical measurement data
• Experience working directly with research teams, study sponsors, or other external collaborators to define measures, data structures, or study data plans
• Experience taking data through statistical analysis to findings, and communicating those findings clearly to non-technical audiences
• Proficiency in Python and/or R
• Comfort working in a Linux or command-line environment
• Experience with Git or another version control system

Preferred

• Experience providing scientific or analytic consulting support to external clients, collaborators, or study teams
• Experience building or maintaining data-processing pipelines or reproducible research workflows
• Experience with neuroimaging data formats or tools, such as NIfTI, DICOM, FSL, Nilearn, or FreeSurfer
• Experience on a large longitudinal or multi-site consortium study, such as the ABCD Study or similar
• Experience with clinical data capture systems such as REDCap or Qualtrics
• Published research that demonstrates methodological rigor in data quality or data definition work
• Experience building tools or systems that let a defined methodology be applied consistently across a team