Top Data Science Jobs in Fayetteville, AR

Lead research and engineering of production-grade LLM/GenAI systems for cybersecurity: design models and architectures, drive data labeling and evaluation, collaborate with product and engineering to deploy scalable solutions, mentor data scientists, set technical strategy, and advance AI safety, red-teaming, and applied ML innovations for detection and operational use.

Lead advanced analytics and ML efforts to extract insights from large-scale historical data, design features and data representations for models and LLM/agentic systems, partner with product and engineering to build data pipelines and prototypes, evaluate AI workflows, and drive innovation through experiments and empirical analysis to inform product strategy.

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.

Build and productionize end-to-end fraud and financial risk models: data acquisition, feature engineering, labeling, training, experimentation, deployment, and monitoring. Research new fraud types, drive product development, support data quality and access, and present analyses to inform product, operations, sales, and marketing.

Lead product analytics efforts by designing and evaluating experiments, building dashboards, and producing statistical insights. Partner with product, design, and engineering to measure product success, identify optimization opportunities, and embed ML-driven personalization into the product.

Build and deploy statistical and machine learning models for the Toast platform. Collaborate with product, engineering, and business teams to identify opportunities, develop data-driven solutions, evaluate models, and communicate insights to stakeholders. Work in a fast-paced environment and contribute to production ML systems and experimentation.

Lead design and delivery of scalable ML systems across the full lifecycle for recommendations, demand forecasting, targeting, and personalization. Collaborate with engineers, product, and stakeholders to set architecture, metrics, and production best practices; mentor data scientists; lead experimentation and deploy/monitor models using cloud and MLOps tooling.

Lead product analytics to inform strategy and optimize user experience: translate business questions into analysis, build reliable analytics infrastructure, run A/B tests and ML/statistical analyses, track funnels and cohorts, support 0-to-1 product launches, and communicate actionable insights to cross-functional teams.

Lead complex modeling projects combining deep learning, LLMs, and traditional techniques. Prototype, deploy, and monitor production models, mentor data scientists, collaborate with engineering/product, and translate results into business impact for insurance customers.

Lead design and production of large-scale ML and agentic AI systems: architect end-to-end data and ML pipelines, build and deploy autonomous agents, design evaluation frameworks, mentor senior talent, set modeling and safety standards, and present technical strategy and impact to leadership.

Lead design and delivery of production-scale AI systems and autonomous agents. Architect end-to-end ML pipelines, deploy NLP/CV/time-series solutions, define evaluation and safety frameworks, mentor senior talent, influence roadmap, and present technical strategy and impact to leadership.

Architect and build a scalable Digital Twin simulations platform: integrate data pipelines, optimize high-throughput simulation systems, orchestrate agentic/LLM-driven simulations, productionize models, and enable real-time visualization with strong engineering best practices.

Lead end-to-end pricing experimentation and strategy for consumer and business products. Design and analyze A/B tests, build pricing models and production-grade data pipelines, partner cross-functionally, and present actionable recommendations to senior leadership.

Lead development and deployment of advanced ML and deep learning models, ensure model validation and MLOps best practices, source and validate data, translate business problems into scalable solutions, collaborate cross-functionally, and mentor data science team members.

Lead development and deployment of large-scale LLM and GenAI solutions for cybersecurity. Drive research strategy, model training, evaluation, safety/red-teaming, and cross-functional productization. Mentor data scientists, set technical standards, and represent the team through publications and thought leadership.

The Senior Data Scientist partners with Customer Success to perform deep-dive analyses, diagnose metric shifts, build predictive models (churn/upsell), apply causal inference and experimentation, measure business impact, and develop AI/LLM solutions. Responsibilities include self-serving across the data stack for extraction, pipelining, and dashboards, defining KPIs, and delivering actionable insights to reduce churn, drive revenue, and improve operational efficiency.

Entefy seeks a Senior Data Scientist with a Master's or PhD in a relevant field, and 3+ years of experience. Responsibilities include delivering advanced analytics, leading teams, and extracting insights from datasets.

Owner of analytics for EHR, revenue cycle, and operations: design and run experiments, analyze financial and operational metrics, investigate billing and account issues, and deliver actionable insights to Product, Operations, Finance, and Customer Experience to improve accuracy, reduce friction, and support growth.

The role involves building and scaling a Closed-Loop Design Program that enhances pre-sales engineering through data science and analytics in supply chain automation.

Develop, train, evaluate, and deploy machine learning models on Databricks. Prepare and maintain large-scale datasets, build Python/SQL workflows, implement ML lifecycle practices (MLflow, model registry, governance), monitor model performance, and communicate insights to stakeholders while collaborating with cross-functional teams.

Designs, analyzes, and interprets clinical trial, RWE, and observational data for a medical device. Develops statistical plans, predictive models, and ensures data quality, regulatory compliance, and traceability. Collaborates with clinical, regulatory, and data teams, supports submissions and publications, mentors interns, and represents the company externally.

Design, implement, and maintain marketing inference models (e.g., MMM and attribution). Analyze large datasets and A/B/uplift experiments with rigorous statistics, build predictive and causal models, partner with marketing to generate testable ideas, and communicate insights to drive marketing decisions.

As a Staff Data Scientist, you will analyze large-scale broadband data, develop and validate ML models, and integrate solutions into Calix Cloud, collaborating with teams for enhanced network intelligence and subscriber experience.

Build models, heuristics, and analytics that optimize model/provider routing and user experience for a large LLM marketplace. Partner with product and engineering to design user-facing data features, define product metrics, run deep analyses, and ship data-driven improvements tied to roadmap decisions. Scale analytical foundation in ClickHouse/dbt.

Design, build, and deploy ML models, LLM/RAG applications, and data pipelines in production. Perform EDA, monitoring, model evaluation, dashboards, and collaborate cross-functionally to translate business needs into scalable AI solutions.