Applied Scientist, AI/ML

QuantCo

20h

About The Position

As an Applied Scientist, AI/ML at QuantCo, you'll bring together advances in AI with rigorous economic and quantitative thinking to build models and systems that power high-stakes decisions across industries. Those systems tackle some of the hardest, most consequential problems our customers face, and you’ll carry the work from initial framing and research through experimentation, model development, and continued iteration in production. We work in areas such as algorithmic pricing, claims management, underwriting, and predictive health. You’ll build on a shared technology base that improves with each new application, while choosing—and when needed, developing—methods to fit the problem. That might mean designing and analyzing experiments; combining predictive modeling with causal inference; developing multimodal models that combine images, text, and structured data; training foundation models on sequences of medical events; or building agents that work with complex data and workflows. The resulting systems run in production at organizations serving millions of people, informing and automating critical business decisions that affect billions of dollars. You’ll have unusual autonomy over how they’re designed and built.

Requirements

• Deep expertise in at least one relevant area—such as machine learning, statistics, econometrics, or causal inference—and an interest in learning and working beyond it.
• Strong command of the mathematical and statistical foundations behind machine learning, statistical inference, and experimental design.
• Fluency in Python and its data and ML ecosystem (e.g., pandas/Polars, scikit-learn, PyTorch/JAX, XGBoost/LightGBM).
• A degree in computer science, economics, statistics, mathematics, physics, engineering, or a related quantitative field.

Nice To Haves

• An advanced degree (MS/PhD) in one of the fields above.
• Hands-on experience training, adapting, or evaluating deep learning and foundation models, or the curiosity and technical foundations to get there quickly

Responsibilities

• Designing and analyzing experiments
• Combining predictive modeling with causal inference
• Developing multimodal models that combine images, text, and structured data
• Training foundation models on sequences of medical events
• Building agents that work with complex data and workflows

Benefits

• Generous compensation package that includes a base salary, bonus, and equity
• Additional location-based benefits

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level