Senior Data Scientist: AI/ML, Data Platform & Imaging

Atrium; Los Angeles (CA); On-site; USD 150,000 - 180,000; Full time

Benefits offered by this job

Medical benefits

Generous PTO

Professional development stipend

Job summary

Atrium, a small biotech company focused on neurodegeneration, is seeking a hands-on Senior Data Scientist to own and build the company’s scientific data platform and analytics infrastructure.

You will transform experimental data into decision-ready insights while partnering with scientists, engineers, and leadership, owning data ingestion, ML pipelines, and reproducible workflows across AWS and related tools.

Qualifications

• 4+ years of industry experience in data science or related roles.
• Strong Python and statistics skills.
• Experience building analytical pipelines and reproducible workflows.
• Experience with version control, testing, and documentation.
• Experience with LLM-based tools or automations.
• Data-driven mindset applied to experimental datasets.

Responsibilities

• Own AWS-based scientific data infrastructure including ingestion, organization, QC, metadata, and access.
• Develop internal AI/LLM tools and analytical workflows.
• Build ML/CV pipelines for microscopy/histology image analysis.
• Establish automated data quality, validation and error-checking processes.
• Analyze diverse datasets using statistical methods to derive insights.
• Build production-ready analytical pipelines.
• Collaborate with Engineering and Scientific teams to align predictions with experiments.
• Maintain ownership and autonomy over the data function.

Skills

Python

Applied statistics

Data pipelines

LLM tools

Version control

Testing

Documentation

ML/Computer vision

Image segmentation

Education

Master's or PhD in a quantitative field

Tools

AWS

S3

Job description

Atrium, a small biotech company focused on neurodegeneration, is seeking a hands-on Senior Data Scientist to own and build the company’s scientific data platform and analytics infrastructure.

You will transform experimental data into decision-ready insights while partnering with scientists, engineers, and leadership, owning data ingestion, ML pipelines, and reproducible workflows across AWS and related tools.