Data Analyst II

Omnicell•Austin, TX

3d•Hybrid

About The Position

At Omnicell, we are transforming the future of healthcare through data-driven innovation, operational excellence, and exceptional customer experiences. As a Commercial Data Insights Analyst, you will play a critical role in helping Technical Support and service organizations turn complex data into meaningful insights that improve customer outcomes, optimize operations, and drive strategic decision-making. This is an exciting opportunity to partner across Technical Support, IT, Data Engineering, Customer Success, and Commercial teams while leveraging advanced analytics, business intelligence, and emerging AI technologies. If you are passionate about solving business problems with data and influencing meaningful change, this role offers a platform to make a measurable impact across the organization.

Requirements

Bachelor's degree in Analytics, Business, Statistics, Information Systems, Economics, or a related field.
Minimum of 2 years of experience in Data Analytics, Business Intelligence, Market Insights, Commercial Analytics, or a related analytical discipline.
Proficiency in SQL and/or statistical programming languages such as Python or R for querying, transforming, and analyzing data.
Experience working with structured operational, commercial, service, CRM, sales, or financial datasets.
Experience creating clear analytical outputs including dashboards, visualizations, summaries, and business recommendations.
Familiarity with business intelligence and data visualization platforms such as Power BI or Tableau.
Demonstrated interest in applying generative AI tools and techniques to improve analytical processes and business outcomes.
Strong attention to detail with the ability to identify, investigate, and resolve data quality issues.
Excellent written and verbal communication skills with the ability to present findings to business stakeholders and leadership.
Ability to manage multiple priorities and projects in a fast-paced, evolving environment.

Nice To Haves

Experience supporting Technical Support, Customer Service, Field Service, Customer Success, or other service operations functions.
Experience working with service, incident, case management, CRM, or ticketing datasets.
Knowledge of platforms such as Salesforce, SAP C4C, Gainsight, ServiceNow, or similar solutions.
Understanding of support and service metrics including SLA compliance, backlog aging, escalation rates, first-contact resolution, mean time to resolution, and customer satisfaction measures.
Experience utilizing customer feedback and survey management platforms.
Experience within healthcare, medical device, medication management, or other regulated industries.
Familiarity with cloud-based data environments such as Databricks, Snowflake, Microsoft Fabric, or similar technologies.
Experience developing executive-level presentations, scorecards, and operational performance reporting.

Responsibilities

Analyze Technical Support and Field Service data to identify trends, patterns, root causes, anomalies, and opportunities to improve operational performance and customer outcomes.
Develop and maintain recurring and ad hoc reporting solutions that measure key operational metrics, including support volume, backlog, response times, resolution times, service level performance, escalation rates, reopen rates, and first-contact resolution.
Evaluate performance across products, customer segments, regions, issue types, support channels, priority levels, and service tiers to uncover meaningful business insights.
Deliver fact-based recommendations that improve support effectiveness, workforce planning, customer satisfaction, and operational efficiency.
Translate business challenges and stakeholder needs into clear business requirements for reporting, systems enhancements, and process improvements.
Partner closely with Technical Support leadership, CDIA, IT, Data Engineering, and Reporting teams to ensure analytics solutions align with business objectives.
Create executive-ready dashboards, presentations, scorecards, and analyses that support operational reviews and strategic decision making.
Monitor customer experience indicators, including CSAT, NPS, customer effort, and support-related feedback, to identify improvement opportunities.
Support AI and data science initiatives through data preparation, exploratory analysis, feature evaluation, and interpretation of analytical outputs.
Collaborate across Commercial Analytics functions, contributing insights that support Sales, Finance, Customer Success, Implementation, and other commercial business areas.