Science Data Analyst
Full Time · Professional CA (+2 more locations)
Salary Range: CAD $68,000 to $98,000 (Montréal) or USD $81,000 to $115,000 (Minneapolis) Annually
About Lasso Informatics
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.
About the Role
Read this part first, it saves us both time: This is a health research role, not business intelligence, financial analytics or management consulting. We are looking for someone who comes from life sciences research and is at home in study design, biostatistics and the messy reality of participant data.
As a Science Data Analyst at Lasso, you sit inside a multidisciplinary research team and help answer real scientific questions. You shape analytical approaches, test them against study design, and turn tangled multi-modal data into findings that hold up. You are comfortable working alongside and communicating with people from every corner of the company, from researchers and software engineers to project managers.
What You'll Do
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Work directly with researchers to define data requirements, resolve quality issues and support reproducible research workflows.
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Conduct statistical analyses in R,Pythonand other tools, applying biostatistical methods suited to the study design, including mixed-effects models and longitudinal techniques.
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Evaluate and contribute to experimental and study design decisions, making sure analyses are valid and that confounds, covariates and sampling are handled properly.
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Apply statistical and computational methods for pattern detection, predictive modeling and data quality assessment across multi-modal datasets.
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Organize and manage datasets and data dictionaries, run QCchecksand conduct preliminary analyses that keep data integrity high.
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Design, configure and maintain dashboards for domain-specific workgroups.
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Produce clear documentation of your methods,pipelinesand findings for scientific and internal audiences.
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Maintain project tracking and help build a culture of rigorous, reproducible science.
Qualifications
Required
