Applied Researcher

Company Overview:

We are building Protege to solve the biggest unmet need in AI — getting access to the right training data. The process today is time intensive, incredibly expensive, and often ends in failure. The Protege platform facilitates the secure, efficient, and privacy-centric exchange of AI training data.

Solving AI's data problem is a generational opportunity. The company that succeeds will be one of the largest in AI — and in tech.

Role Overview

The Applied Researcher bridges the gap between our data assets and our customers' needs in our healthcare vertical. They play a key role in ensuring our datasets are well-matched to the AI models our customers are building and well-understood by those customers. This role requires both healthcare data expertise, extensive experience with statistical analysis, and some customer collaboration.

Key Responsibilities

• Conduct feasibility analyses by querying healthcare datasets to assess patient cohort availability based on complex inclusion/exclusion criteria (i.e. procedures, diagnoses, diversity, longitudinal completeness, regulatory constraints).

• Collaborate directly with customers to understand their use cases and support effective data integration.

• Ensure customers have a clear understanding of the data’s structure, limitations, and strengths.

• Identify gaps in our data offerings and provide insights to our partnerships team on the highest-priority data acquisitions.

• Evaluate potential data partnerships, ensuring the data is high-quality, well-documented, and commercially viable.

About You

• You are curious, tenacious, and proactive.

• You are not bothered by ambiguity but embrace finding patterns in complex environments.

• PhD or MS/BS + industry experience in a quantitative field such as economics, statistics, biostatistics, bioinformatics, computer science, or data science

• Proficiency with programming in R/Python/SQL

• Hands-on experience working with large-scale healthcare datasets, including one or more of the following: imaging, EHR, genomics, claims, or pathology data

• Team-player, no job is too big or too small

• You are an eager scientist and you are not afraid to learn or face a knowledge pit.

• You treat those around you with kindness

Bonus if you have these attributes

• Experience in a customer facing role

• Experience with data optimization techniques such as model-based filtering, multimodal data integration, heuristic filtering, and/or target distribution matching

• Experience applying machine learning or logistic regression techniques to healthcare data.

• Familiarity with third-party data certification or audit processes related to privacy and data quality.

• Ability to think creatively and insightfully about large scale data problems