Top Data & Analytics Jobs in Little Rock, AR

The role involves aligning client data strategies to business objectives, utilizing modern cloud environments and developing analytics-driven strategies to drive growth.

As a Data Analyst at Circle, you'll analyze payments data, create visualizations, develop dashboards, and support decision-making with insights. You'll partner with business teams to identify opportunities for enhancement and communicate findings effectively to stakeholders.

The Senior Data Analyst manages data workflows, resolves data quality issues, and optimizes ETL processes for Arkansas Medicaid's data warehouse while leading a team of data engineers.

Manage a team of Data Analysts to provide actionable insights and dashboards for operational departments, overseeing business intelligence projects and collaborating with other teams to enhance data models.

The Analyst II will provide data-driven insights and support to the sales team, define performance metrics, leverage AI tools, and ensure effective communication of strategies across teams.

The Applied Research Engineer II will lead applied research initiatives, develop algorithms, and collaborate across teams to translate scientific insights into impactful products in human wellness.

As a Lead Product Data Analyst, you'll drive data-informed decision-making across teams, develop data products, collaborate on metrics, and influence product strategies.

The Principal Product Analytics Engineer leads the design and architecture of Toast's product analytics ecosystem, ensuring reliable and scalable data for analysis across various platforms. This role involves creating data frameworks, implementing quality controls, and collaborating with cross-functional teams to support data-driven product development and AI insights.

The Senior Analyst will optimize payment processing workflows by designing dashboards, identifying trends with SQL, and collaborating across teams to enhance payment efficiencies.

Responsible for designing, developing, testing, and optimizing data integration solutions, focusing on financial month-end closure and ongoing production support.

Lead the development and implementation of automation techniques using AI and machine learning to improve life underwriting operations and processes.