AI Data Analysis

We are looking for an AI data analyst who will join the data analysis team to develop and operate Anima’s AI analysis pipelines.



Anima is a Tech.Bio company at the intersection of mRNA biology and AI. We are advancing the mRNA Lightning platform for the discovery of small molecule mRNA drugs and novel mRNA biology targets. Built from the ground up with over a decade of expertise in mRNA biology, the platform integrates mRNA biology with AI imaging technologies to visualize the entire life cycle of mRNA in cells and decode the mRNA biology underlying a disease. Anima’s mRNA Lightning platform is validated by our strategic collaborations with Lilly, Takeda, and AbbVie across therapeutic areas and a pipeline of 20 drug discovery programs.

Key responsibilities:

• Improvement and development of the imaging AI models in Anima.

• Data Analysis pipeline – from images to insights, including preprocessing, segmentation, inference, model scoring, classification, clustering, anomaly detection and more. 

• Keep the company AI evolving to the most updated developments in the field.

• Planning per-project modifications to match biological modeling assays. 

• Introduce new data extraction approaches leverages by AI.

• Suggest new directions toward data collection to serve growth and engagement of AI in the organization.

• Working with both internal and external teams to develop solutions for AI and classical data analysis integration.

Education, experience, and other requirements:

• PhD/MSc in computer science, and computer engineering, with core courses in biology.

• At least 3-5 years of experience in formulating and building AI solutions.

• Proven experience in applying deep learning solutions for extracting insights from images (preferably from the domain of biological/medical measurements).

• Hands-on experience in customizing self-supervised models, clustering methods and foundation models.

• Experience in using Tensorflow, Pytorch, AWS-Sagemaker (Vertex-AI or similar cloud-based AI development platform).

• Excellent understanding of probability theory and applied statistics.

• Attention to details, time management, and organization skills are a must.

• Good programming practices, including object-oriented programming, functional design principles, and version control tools (git, Jira, etc.).

• Actively engages in ongoing professional development to stay current with evolving industry trends and best practices.