Analytics Engineer Internship

Prolaio • Chicago, IL

4h

About The Position

Prolaio believes that continuous learning and collaboration can make a significant difference in how heart care is administered. We are creating smarter ways to address heart disease and heart risks by integrating a connected platform enabled by smart data science to help patients access the care and attention that will inform better treatments and outcomes.
We envision a future where care teams and hospitals can be more effective, the healthcare system can be more efficient, and patients have a better care experience and more fulfilling lives.
This is precision cardiology, and we know it’s within reach.
The Analytics Engineer Intern will support the Data Services team by developing foundational analytical frameworks for our flagship PACE (Proactive Adherence & Continuity Engine) project in decentralized clinical trials. The intern will work with real historical clinical trial data to explore early indicators of participant and site-level non-adherence and contribute to proof-of-concept analyses that inform future product and platform development.
This role is designed to provide hands-on experience working at the intersection of data analytics, clinical trials, and tool design, while delivering meaningful, production-relevant insights.

Requirements

• Currently pursuing a degree in Data Science, Statistics, Computer Science, Biostatistics, or a related quantitative field (senior undergraduate or graduate level).
• Strong proficiency in Python for data analysis (e.g., pandas, numpy, basic visualization).
• Solid understanding of statistics and exploratory data analysis techniques.
• Ability to work with real-world, imperfect datasets and clearly communicate assumptions and limitations.
• Strong written and verbal communication skills.

Nice To Haves

• Exposure to healthcare, clinical trials, or regulated data environments.
• Familiarity with SQL or analytical databases.
• Interest in applied analytics with real-world operational impact.

Responsibilities

• Conduct exploratory data analysis on historical clinical trial datasets to identify potential adherence risk signals at the participant and site levels.
• Develop and document an initial analytical framework for adherence risk signal detection, including assumptions, limitations, and data dependencies.
• Build proof-of-concept analyses or notebooks demonstrating how adherence risk signals could be operationalized in future monitoring tools.
• Collaborate with Data Services leadership and cross-functional partners (Product, Operations) to align analytical findings with real-world workflows and intervention strategies.
• Prepare and deliver a final presentation summarizing findings, feasibility conclusions, and recommendations for next development phases.

Benefits

• Impactful Work: You will join in the fight against heart failure (HF) and hypertrophic cardiomyopathy (HCM) with the goal of extending and saving the lives of our patients while also being at the forefront of changing the healthcare industry through technology.
• Innovative Environment: You will be part of an organization doing something that’s never been done before.
• Professional Growth: You will join a growing team and have a substantial impact on our daily and future operations with the opportunity to continuously learn and grow.
• Collaborative Team: You will be part of a team of collaborative, curious, and committed individuals focused on the collective good, inclusiveness, scientific excellence, and advancing digital health for cardiology.

What This Job Offers

• Career Level: Intern
• Education Level: No Education Listed