Research Scientist

At Waffle Labs, we’re building the foundation models for numbers. While large language models have transformed how we understand unstructured text, the vast world of numerical data—spreadsheets, time series, clinical tables—remains fragmented and underutilized. We’re developing Large Quantitative Models (LQMs): AI systems designed to connect and reason across heterogeneous, sparse datasets to unlock insights in domains ranging from healthcare to supply chains.

We’re looking for a Staff Research Scientist to join our Boston-based team. In this role, you’ll help define the core technical path of LQMs, designing novel algorithms and frameworks that push the frontier of machine learning on structured data. You’ll work closely with other researchers and engineers to turn research into production-ready systems, shaping both our theory and our product.

• Lead research efforts at the intersection of machine learning and numerical data representation, focused on bridging disconnected datasets via latent structure.
• Design and implement novel algorithms for structured data imputation, missing value reasoning, and robust inference from sparse observations.
• Prototype, validate, and iterate on scalable systems in Python for real-world deployment.
• Collaborate closely with engineers and domain experts to translate theory into production-ready solutions.

• Ph.D. in Machine Learning, Operations Research, Applied Mathematics, or a related field is a must.
• Deep expertise in statistical modeling, supervised/unsupervised learning, and optimization techniques.
• Expert-level proficiency in Python and the data science ecosystem (Num Py, Pandas, PyTorch, etc.).
• Experience with missing data imputation, Bayesian methods, or probabilistic programming frameworks is a strong plus.
• Demonstrated ability to drive research agendas and deliver technical innovations independently.
• Strong communication and collaboration skills.
• Highly motivated and intellectually curious.
• Must be authorized to work in the United States, no visa sponsorship.
• Boston-based. This is an in-person position!