Data Scientist (Machine Learning)

Location: Cambridge, Massachusetts, United States; 70% in-office and 30% flexible work model

Salary: $121,600–$194,500 per year, with potential eligibility for bonus, incentive compensation, or equity awards.

Company

hirify.global develops mRNA technology platforms, therapeutics, and vaccines.

What you will do

• Execute research projects using internal and external assay data for biological sciences, RNA sciences, chemistry, delivery sciences, and bioinformatics.
• Build algorithms and machine learning models for sequence-function modeling, RNA design, and LNP design.
• Design and analyze molecular and sequence libraries using experimental design, Bayesian optimization, and active learning.
• Develop, deploy, and maintain ML-powered systems using internal assay data and agentic software development tools.
• Apply software engineering practices including automated testing, code review, documentation, and reproducible workflows.
• Collaborate with data scientists, data engineers, laboratory scientists, software developers, and engineers, and communicate findings internally and externally.

Requirements

• Ph.D. in Computer Science, Biological Engineering, Computational Biology, Biostatistics, Applied Mathematics, or a related discipline with 0–2 years of professional experience, or a Master’s degree with 4+ years of relevant experience.
• Understanding of biotech research and engineering processes, including molecular biology, discovery chemistry, or microscopy.
• Experience building sequence-function or QSAR models and applying them to molecular prioritization.
• Experience partnering with experimental scientists to design, prioritize, and analyze molecular or sequence libraries.
• Strong knowledge of statistics, including experimental design, regression and classification, uncertainty quantification, hypothesis testing, and analysis of noisy biological assay data.
• Ability to work in the stated Cambridge, Massachusetts hybrid environment.

Nice to have

• 2+ years of experience delivering data science projects.
• Fluency in Python and the scientific Python ecosystem, including Jupyter, Pandas, scikit-learn, and PyTorch.
• Experience with neural vision models, neural language models, diffusion models, or graph neural networks.
• Experience integrating external data sources and conducting interdisciplinary research collaborations.
• Familiarity with AWS, Docker, Git, documentation practices, and scientific publication or method development.

Culture & Benefits

• Healthcare and voluntary benefit programs.
• Fitness, mindfulness, and mental health resources.
• Family planning support, including fertility, adoption, and surrogacy benefits.
• Paid vacation, volunteer days, sabbatical, global recharge days, and year-end shutdown.
• Savings and investment programs, plus location-specific benefits.
• In-person collaboration, teamwork, and direct mentorship through the 70/30 working model.