Bioinformatics Machine Learning Scientist

Pay Rat Range: 51-61/hr
*depending on experience

Job Description:
The successful candidate will work closely with stakeholders in the Quantitative Medicine and Genomics (QM&G) organization to develop predictive AI/ML models using large-scale transcriptomic and imaging datasets to elucidate drug mechanism of action (MOA). Key responsibilities can include ingesting public data, performing data clean-up to ensure model compatibility, integrating external and internal datasets, and optimizing multi-model models. This role offers the opportunity to make a direct impact on drug development by delivering innovative data science solutions across cross-functional projects.

Key Responsibilities:
• Support senior analysts in implementing, training, and troubleshooting AI models.
• Ingest, clean, and preprocess large-scale transcriptomic and imaging datasets for AI workflows.
• Collaborate with scientific and technical teams to translate biological questions into computational solutions.
• Document processes and outcomes ensuring reproducibility and transparency.
• Assist in interpreting model outputs to advance the understanding of drug MOA.
• Work with agility on time-bound projects with critical deliverables.

Qualifications:

• MS degree (5+ years of experience) or PhD (0 years of experience) in a quantitative field (Bioinformatics, Computer Science, Computational Genetics, Biostatistics, AI/ Machine Learning Engineer or other field with a strong quantitative and computational background)Proficiency in Python and standard ML libraries
• Proficiency working on HPC or cloud environments.
• Domain knowledge in bioinformatics/computational biology
• Strong attention to detail, documentation, and communication skills
• Ability to independently execute and troubleshoot research plan
Preferred technical skills:
• Experience with NumPy, Pandas, Scikit-learn, Matplotlib, and seaborn.
• Experience with TensorFlow, and/or PyTorch
• Experience with git for version control and collaboration
Additional technical skills:
• Experience with OpenCV, Scikit-image, and computer vision deep learning models
• Experience with multi-modal models

*CO/NYC candidates might not be considered