Top Data Science Jobs in Las Vegas, NV

Design and evaluate predictive and generative models, extract insights from disparate clinical and product data, build and partner on data pipelines, run rigorous evaluations and experiments, and deliver time-sensitive ad hoc analyses to product, engineering, and clinical stakeholders.

Lead technical vision and delivery of enterprise-scale learning intelligence and agentic AI: architect measurement and personalization systems, build skill graphs and taxonomies, define causal and experimentation strategies, ensure model evaluation/observability and responsible AI, partner cross-functionally, and mentor data science teams to drive measurable learner and business outcomes.

Hands-on senior data scientist splitting work between SQL Server data engineering (ETL, pipeline modernization, data quality) and analytics delivery (Power BI semantic models, dashboards, statistical and predictive modeling). Duties include designing migration options, implementing Python-based cleansing and reproducible analytics, building ETL/deployment processes, responding to ad hoc leadership data requests, and documenting systems for stakeholders. Must obtain VA background/PIV and be a U.S. citizen.

Lead development of rigorous evaluation frameworks and metrics for autonomous systems, analyze large on-road and simulation datasets, detect metric drift, prototype statistical and ML methods, correlate simulation and real-world results, and drive actionable improvements to testing, sampling, and launch-readiness decisions while mentoring teammates and advising stakeholders.

Design, build, and deploy ML models across diverse use cases; work with managed cloud ML platforms and containerized solutions; collaborate with engineers on production integration and MLOps best practices; preprocess and analyze large datasets; mentor teammates and influence technical direction; translate complex ML concepts for technical and non-technical stakeholders.

Lead end-to-end client ML engagements: scope problems, design, build, and deploy production ML solutions across cloud and containerized stacks. Lead and mentor small teams, manage client relationships, evaluate emerging tools, and ensure models are production-ready and explainable to technical and non-technical stakeholders.

As a Lead Data Scientist, you'll design experiments, build predictive models, and lead a team while shaping data-driven strategies to enhance AI deployments.

Design, develop, and deploy time-series and machine-learning forecasting models (ARIMA, SARIMA, ETS, XGBoost, LightGBM) for demand planning, inventory, and sales forecasting. Perform large-scale SQL data processing, operationalize models in cloud environments (Azure preferred), present insights, and lead client workshops.

The role involves building and validating Marketing Mix Models and geo-experiments, managing measurement infrastructure, and communicating insights to stakeholders.

Design and build custom measurement products by combining Nielsen datasets; develop statistical and ML models; write production-quality SQL, Python, and PySpark; build reusable ETL pipelines; use AI tools and design agentic workflows; translate stakeholder requests, document methodology, and collaborate with Research, Sales, and Insights teams.

Design, build, validate, deploy, and monitor machine learning and generative AI solutions for healthcare and life sciences. Work with EHR, claims, and registry data to produce clinical predictions, operational optimizations, and LLM-powered applications. Translate results for stakeholders, document best practices, and mentor client teams.

Design, develop, and deploy production-grade generative AI and agentic systems (LLMs, RAG, AI agents). Build document intelligence, retrieval pipelines, vector search, and monitoring frameworks. Collaborate with risk, compliance, product, and engineering to deliver scalable, governed GenAI solutions in regulated environments.

As a Senior Data Scientist, you'll lead projects leveraging data to enhance healthcare outcomes, mentor team members, and align data efforts with business goals.

The Senior Data Scientist will analyze and optimize marketing funnels, build statistical models, conduct experiments, collaborate with teams, and mentor junior members.

Design and build predictive models, AI tools, and data visualizations for CMS healthcare initiatives. Analyze quantitative and qualitative data (Medicare claims, public datasets, web analytics), perform feature engineering, anomaly detection, and provide insights to support product design and price-transparency tools. Collaborate with designers, product owners, and engineers in an agile environment.

Senior individual contributor who builds statistical models and experiments to optimize acquisition, conversion, retention, and lifetime value. Partners with Product, Marketing, and Engineering to define data requirements, analyze A/B tests, perform cohort and funnel analyses, communicate findings to stakeholders, and mentor junior team members while contributing to analytics best practices.

As a Senior Data Scientist, you will develop statistical models and machine learning algorithms to improve patient enrollment and trial management while ensuring compliance in a healthcare data environment.

Build and maintain large commercial datasets and predictive/forecasting models (BigQuery, dbt, SQL, Python). Design causal and experimental analyses to measure promotion impact and price elasticity. Partner with commercial, finance, and executive stakeholders to inform pricing, distribution, and investment. Deploy LLMs and AI agents to classify unstructured data and build tools that democratize data access.

Embedded on a core business team, own analytics end-to-end: define problems, design metrics and experiments, pull and analyze data, build reports, surface insights, and drive measurable outcomes by recommending and influencing product, growth, and operations decisions.

Embed within a core business area to define problems, build metrics, run analyses and experiments, create reports, and drive data-driven recommendations to improve product, growth, AI/automation, or partnerships outcomes.

Lead end-to-end delivery of strategic data science and AI projects: define business problems with stakeholders, prepare large datasets, build and deploy predictive, prescriptive, and generative AI models (including LLMs), implement prompt engineering and fine-tuning, ensure production-grade code and ML lifecycle practices, present insights to senior stakeholders, and promote responsible AI and adoption across teams.

Own and evaluate national and subnational projection models using large-scale healthcare claims. Build evaluation studies, diagnostic tooling, and benchmarks. Investigate customer-raised anomalies, communicate methodology, review model code with engineering, and maintain documentation to ensure model quality and trust.

Lead development and operationalization of measurement products (MMM, incrementality, insights, recommendations). Build, deploy, and maintain production-grade statistical and ML systems, debug end-to-end data and model issues, evaluate methodologies, and partner with engineering, product, and customer teams to improve measurement accuracy and reliability. Provide customer-facing explanations and support for measurement outputs.

Lead end-to-end machine learning and advanced analytics projects: frame problems, build and deploy predictive/prescriptive models, design ETL pipelines, create dashboards and A/B test metrics, and deliver actionable insights to business stakeholders to improve fleet, pricing, and ridesharing products.

The Senior Data Scientist will manage data collection, design study protocols, train juniors, lead report development, and support innovative analytics tools.