Applied Scientist (ML)

TL;DR

Applied Scientist (ML): Building and measuring ML systems for health engagement programs with an accent on prediction, prioritization, and uplift modeling. Focus on designing A/B tests and integrating LLM-powered workflows to improve real-world member outcomes.

Location: Austin, TX

Company

hirify.global is a digital health company pioneering biomarker intelligence by combining AI-powered technology with human insight to deliver personalized health answers.

What you will do

• Build and improve ML models for engagement and operational workflows, focusing on prediction and prioritization.
• Develop models for uplift and related decisioning use cases.
• Design and analyze A/B tests and other measurement approaches to evaluate incremental impact.
• Define and monitor model performance, business impact, and overall system health.
• Partner with stakeholders to define success metrics and translate findings into actionable decisions.
• Evaluate AI- and LLM-powered workflows for deployment in production settings.

Requirements

• 5+ years of experience in Applied Science, Data Science, ML, or Decision Science.
• Strong hands-on experience training, evaluating, and improving ML models.
• Proven expertise in designing and analyzing A/B tests.
• Proficiency in Python and SQL.
• Experience measuring model and product performance in production environments.
• Ability to communicate complex technical findings clearly to cross-functional stakeholders.

Nice to have

• Experience with causal inference or uplift modeling.
• Knowledge of LLMs, AI agents, or automated production workflows.
• Experience working within healthcare or other regulated environments.
• Familiarity with Snowflake, dbt, Airflow, and GitLab.