When you’re the best, we’re the best. We instill an environment where employees feel engaged, satisfied and able to contribute their unique skills and talents while living and working as their authentic selves. We provide extensive opportunities for personal and professional development, building both employee competence and organizational capability to fuel exceptional performance through an inclusive environment both now and in the future.

Applications submitted without a personal statement will not be considered. Please upload a single combined PDF containing both your resume and personal statement in the Resume/CV section of the application in the following order:

1) Resume

2) Personal statement (View details below)

Required application materials:

1) Resume

2) Personal statement (1,000 words max)

• Why Vizient
• Why this fellowship 

Summary

In this role, you will be paired with a Vizient executive as a mentor for the duration of this one-year program. You will be responsible for data science projects across the healthcare domains of clinical & operations, supply chain, pharmacy, and healthcare strategy. You will work with executive mentor(s) and data scientists to match projects to your interests and goals, with an aim to improve operations, enhance products, or generate new insights.

Responsibilities

• Work with internal data science teams on assigned projects.
• Develop data science approaches, including machine learning models, improve understanding and predict health care outcomes, conduct data management and other assigned tasks.
• Collaborate with internal Vizient staff and leaders, and external stakeholders including Vizient clients, vendors, and other third parties.
• Conduct self-directed research into healthcare data topics.
• Participate in client-facing meetings and ‘voice-of-customer’s work to gain understanding of Vizient business needs.
• Participation in cross-functional project assignments and present a capstone project or summary of projects to peers and mentors at the end of the Fellowship. 

 Qualifications

• Relevant degree preferred: Master’s degree in data science, statistics, medical/health informatics, or related field desired.
• No previous work experience is required.
• Demonstrated technical skills, including strong proficiency with programming languages such as Python, R, or SAS, and strong proficiency with database design involving SQL, are required.
• Demonstrated good proficiency in quantitative skills necessary for data analysis and machine learning model development (e.g., statistical/Bayesian inference, mathematics, computer science, etc.) are required.
• Strong familiarity and practical experience with Generative AI models (Large Language Models, Agentic Workflows, and other frameworks) is preferred.
• Solid understanding of machine learning operations is preferred.
• Experience working with health care data (EHR/EMR data, medical terminologies, etc.) is strongly preferred.
• Strong communication and project management skills are preferred. 

Applications submitted without a personal statement will not be considered. Please upload a single combined PDF containing both your resume and personal statement in the Resume/CV section of the application in the following order:

1) Resume

2) Personal statement (View details below)

Required application materials:

1) Resume

2) Personal statement (1,000 words max)

• Why Vizient
• Why this fellowship 

Estimated Hiring Range:

At Vizient, we consider skills, experience, and organizational needs in our compensation approach. Geographic factors may adjust the range estimate and hires typically fall below the top range. Compensation decisions are tailored to individual circumstances. The current salary range for this role is $51,900.00 to $87,900.00. This position is also incentive eligible.

 Vizient has a comprehensive benefits plan! Please view our benefits here:

 http://www.vizientinc.com/about-us/careers

Equal Opportunity Employer:   Females/Minorities/Veterans/Individuals with Disabilities

The Company is committed to equal employment opportunity to all employees and applicants without regard to race, religion, color, gender identity, ethnicity, age, national origin, sexual orientation, disability status, veteran status or any other category protected by applicable law.