Top Remote Data Science Jobs in Raleigh, NC

Lead development of production-grade fraud and identity risk signals from high-scale device, network, browser, mobile, API, and behavioral telemetry. Define evaluation methods, build scalable feature engineering, investigate adversarial signal patterns, influence telemetry and production readiness, mentor data scientists, and drive technical direction for robust, explainable, low-latency decisioning systems.

Develop ML features, models, and analytical methods from device, network, browser, mobile, session, and behavioral telemetry to detect fraud and improve identity confidence. Handle large-scale, noisy, high-cardinality data, design validations, assess drift and leakage, collaborate with engineering/product/risk for production rollout, document models and features, and mentor junior team members.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

The Staff Data Scientist will own the analytical strategy for Firefox, driving data-informed decisions through measurement frameworks, experiments, and user growth analysis, while mentoring other data scientists.

The Staff Data Scientist will lead analytical strategies for Firefox, focusing on product growth, measurement frameworks, and mentoring data scientists while guiding data-driven decisions.

Design and evaluate causal inference experiments and causal ML models to measure product impact, optimize resource allocation, and inform support operations. Build, deploy, and iterate statistical/ML models, analyze tradeoffs, collaborate cross-functionally, and communicate insights to influence decisions and scale data science capabilities.

Build, evaluate, and deploy LLM/ML models and synthetic datasets to improve Community Support. Identify opportunities via data exploration, analyze structured and unstructured data, automate LLM evaluation, personalize experiences, and collaborate cross-functionally to drive product and operational impact.

The Data Scientist will build machine learning models to enhance claim audits, optimize performance, and improve healthcare decision-making by analyzing complex data sets.

The Staff Data Scientist will advance machine learning models to optimize claim audits and improve business outcomes in healthcare.

The Staff Data Scientist will lead the development and deployment of ML and GenAI systems to detect billing errors and fraud in healthcare payments, collaborating with cross-functional teams.

The Data Scientist will develop tools for enhancing signature management capabilities, integrate diverse data holdings, and leverage AI/ML solutions for operational support.

Develop a tool to enhance signature management capabilities and integrate diverse data holdings, leveraging AI/ML solutions to meet operational needs.

Customer-facing data scientist advising customers on experiment design, statistical methodology, and experimentation architecture; running and analyzing A/B tests; building scalable experimentation programs; creating repeatable frameworks and technical enablement; partnering with Sales, Solutions Engineering, Product, and Engineering to drive customer success.

Build and productionize ML models and data infrastructure to analyze millions of chaos engineering experiments, detect and explain failures, recommend automated remediation, and integrate AI-driven failure analysis into Gremlin's product using techniques like causal inference, graph ML, time-series modeling, and reinforcement learning.

Lead and deliver end-to-end data science projects: design, build, deploy, and monitor ML/statistical models for credit risk, pricing, collections, and fraud. Partner with cross-functional teams to integrate models into production, set model development standards, mentor engineers, and maintain reliable ML pipelines and monitoring systems.

Lead development of orthomosaic tile imagery products for FireSat and SBEM: design and implement scalable mosaicking, orthorectification, and radiometric normalization algorithms; write production-ready code; author technical and customer-facing documentation; validate scientific quality; engage stakeholders and act as product owner for SBEM granule product; collaborate with engineers and scientists.

Lead radiometric calibration and image processing for multispectral infrared instruments, commission FireSat satellites, and develop/execute SBEM calibration plans. Implement production-ready pipelines, perform R&D to improve calibration, write production-quality code, and collaborate cross-functionally to maintain operational remote sensing data products and services.

The Data Scientist will build predictive models, drive forecasting, design experiments, and translate findings for stakeholders, optimizing healthcare operations.

Perform statistical analysis, predictive modeling, and data visualization on workforce and training data. Build dashboards, produce ad hoc analyses and decision-support products, advise on data governance/privacy, and collaborate with stakeholders to define metrics, deliverables, and reproducible analytic workflows.

Use statistical and causal inference methods to build, implement, and monitor marketing models (Bayesian MMM, multi-touch attribution), analyze A/B and uplift tests, partner with marketing to test and drive data-informed decisions from large web-product datasets.

Lead and grow a 4–6 person data science team, set the roadmap, deliver marketplace forecasting and production ML (matching, scoring), embed data science cross-functionally, and establish modeling, experimentation, and monitoring best practices.

Build and deploy machine learning models on large healthcare datasets, extract actionable insights, develop scalable data processing systems, collaborate with cross-functional teams, and communicate findings to stakeholders to improve patient outcomes.

Embed with a business unit to define problems, run analyses, design experiments, build reports, surface insights, and drive data-informed decisions across growth, product, AI, or partnerships.

Embed with a core business unit to define problems, design experiments, build reports, run analyses, surface insights, and drive data-informed decisions end-to-end across growth, product, AI/automation, or partnerships.

Design, validate, and operationalize predictive and machine learning models; mine and analyze large datasets; create visualizations and statistical validation; collaborate with teams to integrate solutions and communicate results to stakeholders.