Remote Biomedical Data Scientist information
See Portland, OR salary details
$39.8K - $55.1K
2% of jobs
$55.1K - $70.4K
3% of jobs
$70.4K - $85.8K
6% of jobs
$85.8K - $101.1K
9% of jobs
$106K is the 25th percentile. Wages below this are outliers.
$101.1K - $116.4K
15% of jobs
The median wage is $126.6K / yr.
$116.4K - $131.7K
22% of jobs
$140.2K is the 75th percentile. Wages above this are outliers.
$131.7K - $147.1K
32% of jobs
$147.1K - $162.4K
3% of jobs
$162.4K - $177.7K
4% of jobs
$177.7K - $193.1K
1% of jobs
$193.1K - $208.4K
2% of jobs
How much do remote biomedical data scientist jobs pay per year?
As of Aug 19, 2026, the average yearly pay for remote biomedical data scientist in Portland, OR is $130,165.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,500.00 and $144,200.00 per year, depending on experience, location, and employer.
A Remote Biomedical Data Scientist is a professional who analyzes complex biological and medical data from a remote location, often working from home or another offsite setting. They use statistical methods, machine learning, and computational tools to interpret data related to healthcare, genomics, clinical trials, or medical imaging. Their work helps improve patient outcomes, advance scientific research, and inform healthcare decisions. Remote roles typically require strong communication and collaboration skills to work effectively with multidisciplinary teams online.
To thrive as a Remote Biomedical Data Scientist, you need expertise in statistics, machine learning, data analysis, and a solid background in biology or biomedical sciences, often supported by an advanced degree. Familiarity with programming languages such as Python or R, experience with bioinformatics tools, and knowledge of data management systems are typically required. Strong problem-solving skills, effective communication, and the ability to collaborate virtually are essential soft skills in this role. These competencies enable accurate interpretation of complex biomedical data and facilitate impactful research or product development in remote, interdisciplinary environments.
Remote biomedical data scientists often encounter challenges such as collaborating effectively with cross-functional teams, managing large and sensitive datasets, and ensuring clear communication with researchers and clinicians. To address these, it's important to utilize secure data-sharing platforms, maintain regular virtual meetings, and document analyses thoroughly. Additionally, leveraging collaborative tools and staying updated on data privacy regulations can help ensure smooth workflows and compliance.
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