onsite
Data Scientist, Lab & Protein Data - adaptyv
Data Scientist
Data Scientist to develop AI-driven pipelines for protein design and experimental automation, leveraging Python, machine learning, and cloud infrastructure to translate computational hypotheses into lab results.
About the role
Key Responsibilities
- Design and implement machine‑learning models for protein sequence generation, structure prediction, and functional annotation.
- Develop data pipelines that ingest, clean, and integrate high‑throughput lab assay data with computational predictions.
- Collaborate with AI agent teams to close the loop between in‑silico design and automated laboratory execution.
- Deploy scalable analytics and model serving solutions on cloud platforms (e.g., AWS) to support real‑time experiment feedback.
- Perform statistical analysis and validation of experimental outcomes to iteratively improve model performance.
Requirements
- Strong proficiency in Python and its scientific stack (NumPy, pandas, scikit‑learn, PyTorch/TensorFlow).
- Experience building and deploying machine‑learning models for protein or other biological data.
- Solid understanding of bioinformatics concepts, protein biochemistry, and experimental assay data.
- Hands‑on experience with cloud services (AWS) and containerization for reproducible pipelines.
- Excellent problem‑solving skills and ability to work cross‑functionally with AI, engineering, and wet‑lab teams.
Skills
pythonmachine learningdeep learningaws