Data Operations Analyst

Salud Revenue Partners•West Lafayette, IN

1d•Hybrid

About The Position

Salud Revenue Partners (Salud) is a technology-enabled service company with leadership and a high-performance culture that partners with healthcare providers nationwide to improve their revenue cycle performance. Our vision is to be a national model for the delivery of revenue cycle services. We are at the forefront of innovation, applying next generation process automation and artificial intelligence to focus on the most productive work to help healthcare organizations resolve difficult accounts receivable, find gold in zero balance accounts, achieve the highest coding accuracy, and carry out patient-centered solutions to self-pay. At Salud Revenue Partners, you can work for an organization dedicated to your employee development as well as delivering unparalleled results for our customers. We give staff objectives, exceptional training, and technology-enabled resources to accomplish goals and then set them free to get the job done. We encourage fresh ideas and a collaborative approach to delivering industry-leading solutions to clients. What do our staff say about Salud? In May 2025 we were certified a Great Place to Work (for the 3rd year in a row), below are a few of our survey results: 97% of our employees say this is a great place to work! 97% of our staff say, "When you join the company, you are made to feel welcome." 97% of our employees say, "When I look at what we accomplish, I feel a sense of pride." 99% of our employees say, "People are encouraged to balance their work life and their personal life." Role Summary The Data Operations Analyst serves as a key partner to the Data Science Strategic Leader, owning high-impact, evolving initiatives across analytics, operations, and systems. This role is responsible for identifying opportunities, conducting analysis, and driving solutions that improve performance, scalability, and insight across the division. The ideal candidate takes initiative, enjoys solving complex problems, and exercises strong judgment in prioritizing and delivering high-quality outcomes while working in close partnership with leadership.

Requirements

Bachelor's degree in data analytics, business, information systems, or a related field.
2-5 years of experience in a data analyst, business analyst, or similar role preferred.
Experience working on cross-functional projects and managing multiple priorities.
Proficiency in data analysis tools such as Excel, SQL, and Power BI (or similar).
Ability to work with and integrate data from multiple systems.
Strong analytical and critical-thinking skills.
Excellent communication skills, with the ability to translate complex data into clear insights.
Ability to work independently, take initiative, and thrive in a fast-paced, ambiguous environment.
Stress Management/Composure
Results Driven
Technical Capacity
Problem Solving/Analysis
Customer/Client Focus
Teamwork Orientation
Collaboration Skills
Time Management
Communication Proficiency

Nice To Haves

Master's preferred.

Responsibilities

Strategic & Ad Hoc Problem Solving Own and execute high-priority, cross-functional projects that require thoughtful analysis and solution development.
Identify gaps, inefficiencies, and opportunities within the data science function.
Translate ambiguous business questions into structured analysis and actionable recommendations.
Data Analysis & Insight Generation Analyze data to uncover trends, risks, and opportunities that inform decision-making.
Build and maintain reports, dashboards, and analytical models using tools such as SQL, Excel, and Power BI.
Partner with data analysts and other team members to ensure consistency, accuracy, and clarity of outputs.
Operational Analysis & Improvement Evaluate workflows and systems to recommend improvements that enhance efficiency and scalability.
Support the implementation of process improvements and help standardize best practices.
Support prioritization of work by identifying high-value opportunities and bringing forward data-driven recommendations.
Leadership Support Act as a thought partner to the Data Science leader, helping shape priorities and approaches.
Prepare analyses, insights, and materials for internal and client-facing discussions.
Drive initiatives through to completion, proactively identifying risks and ensuring progress and outcomes are clearly communicated.
Project Ownership Manage multiple initiatives simultaneously, balancing competing priorities effectively.
Ensure projects are completed with high quality and within established timelines.
Communicate progress, risks, and outcomes clearly to stakeholders.