Top Data & Analytics Jobs in Fayetteville, AR

Build and own the reporting and insight layer: write optimized Redshift queries, build dashboards, monitor model feedback signals, triage and prioritize investigations for data science, maintain ETL pipelines ingesting semi-structured data, and enable Customer Success with clear metrics and onboarding checks. Move into model validation and automation to scale analytic workflows.

The Business Analyst will gather requirements from clients, support project lifecycles, conduct demos, and manage change, while utilizing ServiceNow. Responsibilities include documentation and relationship building.

Lead and build Newfire's clinical data engineering practice: define architectures, reusable patterns, and governance; own analytics and transactional pipelines; provide hands-on technical leadership with Databricks/Snowflake/dbt; mentor and grow the team; partner commercially to identify opportunities; and integrate practical AI capabilities for healthcare data use cases.

The Product Analyst will measure results and deliver insights on new AI products, identify opportunities, and guide product strategy through data analysis and visualization.

Manage the end-to-end data issue lifecycle for North America: intake, triage, root cause analysis, remediation planning and execution oversight. Produce IMR reporting and dashboards, maintain audit-ready records, engage stakeholders, and improve IMR processes and tooling to strengthen data quality and controls.

Support design and delivery of operational, analytical, and AI-ready data products across the full lifecycle: discovery, requirements, semantic modeling, data mapping, testing, deployment, governance, data quality, documentation, and adoption. Work with stakeholders, engineers, governance and AI teams to ensure reusable, trusted datasets and semantic layers; assist UAT, lineage, metadata, and change management, and use AI-assisted tools to accelerate analysis and product design.

Own Mixpanel and partner closely with Product to turn product-level data into decision-grade insights. Define instrumentation and event taxonomy, build dashboards and notebooks, run cohort and retention analyses, design and analyze A/B tests, and collaborate with data engineers to model product event data. Document metrics, maintain a living glossary, and translate findings into actionable product recommendations.

Design and maintain enterprise information architecture, including domain models, taxonomies, ontologies, and metadata to make data AI-ready. Operationalize models via enterprise data catalog (Alation), resolve semantic conflicts, define metadata standards, and partner with analytics and AI teams to enable governed, explainable AI and downstream BI/LLM use cases.

The Senior Bioinformatics Data Engineer will build data pipelines, implement clinical data ingestion, and optimize platform infrastructure while ensuring data quality and compliance with legal standards.

Own and maintain data products end-to-end for sector teams, analyze large datasets, refine methodologies, automate workflows using AI and tooling, collaborate with Research, Engineering, and Product, and deliver accurate, client-facing insights and improvements.