Top Remote Data Science Jobs in Provo, UT

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.

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

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.

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.

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.

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

Lead the technical development and automation of enrollment forecasting models, collaborating with various departments to enhance decision-making and forecast accuracy.

The Forward Deployed Marketing Data Scientist will work with AI customers and engineering teams to optimize AI-driven marketing campaigns through data analysis, diagnostics, and communication of insights to stakeholders.

Design, build, and validate predictive models on large transaction datasets to support Sales and B2B Marketing. Lead experiment design and evaluation, produce stakeholder-facing analyses and reports, and deploy data science projects to production to drive business impact.

Apply machine learning to large datasets to build predictive models, perform data mining, and develop algorithms. Analyze results, create visualizations, and provide insights to inform business decisions.

Build, monitor, and maintain production ML models and LLM/agent systems. Analyze complex datasets, develop proofs of concept, collaborate with stakeholders, and align work to sustainability business needs.

Deploy and validate NEXUS in customer environments, perform end-to-end data and feature engineering, benchmark against baselines (XGBoost/LightGBM), optimize models for business impact, handle last-mile integrations (VPC/on‑prem/air-gapped), and translate field insights into product improvements while liaising with stakeholders.

Contract data scientist to remotely gather, extract, and analyze technical information about AI models, benchmarks, data centers, and companies. Tasks include reading ML papers, tracking leaderboards, processing satellite images/permits, compiling infrastructure details, and producing data insights for research and policy. Part-time (10–30 hrs/week), flexible schedule with occasional Pacific Time meetings.

As a Compliance Data Scientist Co-op, you will automate data processing, enhance Power BI reports, and utilize AI for compliance improvements.

As a Senior Data Scientist, you'll optimize search relevance, retrieve content, analyze data, and collaborate with teams to enhance product strategies.

As a Staff Data Scientist, you will lead experimentation strategies, apply advanced causal inference techniques, and guide analytical insights to drive product and business decisions.

Lead enterprise-level Medicare Stars forecasting and cutpoint analytics. Design statistical and ML/time-series models, build end-to-end Snowflake/Python/SQL pipelines, integrate LLM-enabled analytics, produce executive dashboards, and partner with Product, Clinical, and Quality leaders to translate forecasts into business strategy and risk mitigation.

Senior individual-contributor leading end-to-end analytics for Medicare Stars: designing forecasting and performance models, building enterprise dashboards (Tableau/Looker), implementing GCP data solutions, ensuring data quality, and delivering executive insights to drive Stars performance and business impact across clinical, product, and data teams.

Lead clinical data management activities: coordinate eCRF planning, database development, UAT, edit checks, external data integration, risk assessment, team coordination and training, budget oversight, SOP compliance, and process improvements for clinical studies.

Lead development of rigorous evaluation frameworks and statistical methods to measure and validate autonomous vehicle system performance. Monitor metric reliability, detect drift, identify edge cases, correlate simulation and on-road results, and feed scenarios into simulation catalogs. Partner with safety, systems, and engineering teams to inform launch decisions, build self-service tooling for developers, and mentor peers. Introduce scalable ML methods where appropriate to improve evaluation rigor and coverage.

As a Lead Data Scientist, you will design and implement scalable data pipelines and analytics capabilities while leading technical decisions across data workflows, ETL processes, and statistical modeling in the GCP environment.