Senior Enablement Analyst

Truveta•Seattle, WA

15h•Remote

About The Position

The Enablement Analyst helps customers translate complex data products into practical, high-value workflows. This role partners closely with customer teams, solution engineers, product, and support to create clear, usable enablement materials that help customers understand the data model, create omni-modal patient journeys, and build successful analytics and machine learning use cases. The ideal candidate combines strong technical fluency with clear communication and customer empathy. They can explain complex data concepts in a simple way, create documentation and notebooks that are easy to follow, and proactively identify where customers may need guidance to move from data access to insights.

Requirements

Experience in customer enablement, solutions consulting, analytics, or data science.
Strong ability to explain complex technical concepts in plain language.
Familiarity with healthcare data, EHR data, and images strongly preferred.
Comfort working with notebooks, data dictionaries, SQL, Python, or similar analytical tools.
Experience supporting technical customers in building analytics or ML workflows using omni-modal data.
Strong collaboration, organization, and communication skills.

Nice To Haves

Experience with patient journey analysis, clinical data modeling, or omni-modal data.
Familiarity with imaging metadata and how it connects to clinical records.
Background in supporting enterprise or strategic customers with technical enablement.
Experience creating customer-facing materials for highly technical audiences.

Responsibilities

Develop customer-facing enablement content, including notebooks, guides, FAQs, slide decks, and walkthroughs.
Facilitate large exports of omni-model data to customer environments.
Help customers understand the data model, including clinical, administrative, notes, and imaging tables and how they relate to one another.
Explain de-identification concepts, quasi-identifiers, and privacy considerations in a way that is practical for customer workflows.
Support customers using data for analytics, patient journey analysis, and predictive modeling using machine learning.
Create examples and best-practice materials that show how to structure cohorts, link tables, and validate outputs.
Partner with internal teams to identify common customer questions, gaps, and opportunities for improved documentation.
Translate technical product behavior into clear customer messaging, especially around profiles, date handling, suppression logic, and ML readiness.
Monitor customer needs and recommend enablement strategies that improve adoption and reduce friction.
Contribute to a scalable library of reusable enablement assets for technical users.