Top Data Science Jobs in Denver & Boulder, CO

The Data Scientist will analyze user behavior, create segmentation strategies, design experiments, and track business metrics to drive growth in a SaaS company.

Lead end-to-end data science projects, develop machine learning models, collaborate with stakeholders, mentor team members, and communicate insights effectively.

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.

As a Data Scientist at SentiLink, you'll develop fraud detection models using machine learning, engage in product development, and support analysis across teams. This role emphasizes hands-on technical work and end-to-end project ownership in a fast-paced environment.

Develop and operationalize graph-based analytics for fraud detection and investigative analysis. Build graph models, apply graph algorithms and ML to detect anomalies, support entity resolution, create visualizations and dashboards, and collaborate with investigators and stakeholders to deploy and maintain production solutions.

Lead end-to-end data science for a priority vertical (Insurance), building, validating, and deploying ML models that drive ROAS and lead quality. Partner with stakeholders and ML engineering to monitor live performance, iterate models, and identify new modeling opportunities to improve revenue and media efficiency.

The Sr. Football Data Scientist will build, deploy, and refine analytical models for football insights, managing large datasets and collaborating with teams for high-quality analytics solutions.

As a Staff Data Scientist, you'll develop and deploy machine learning models to enhance renter experiences and optimize property partnerships, collaborating across teams to translate data insights into actionable strategies.

As a Data Scientist III, you'll build customer identity systems, develop recommendation models, predictive analytics for customer behavior, and collaborate with ML Ops and Data Engineering.

This role involves leading data science projects, designing technical solutions, implementing machine learning methodologies, and developing data workflows for cybersecurity applications.

The Data Scientist II will develop machine learning algorithms, architect data solutions, and support cybersecurity initiatives by analyzing complex data sets.

As a Senior Data Scientist, you will lead high-complexity projects, develop ML and NLP solutions, and collaborate across teams to drive business impact through statistical modeling and data analysis.

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.

Embedded on a core business team, define and prioritize analytical problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed product, growth, and partnership decisions end-to-end.

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

Embed in a core business area to define problems, build metrics, run analyses and experiments, surface insights, and drive outcomes by recommending and executing data-driven actions end-to-end.

Own analytics for an embedded business unit end-to-end: define problems, set metrics, build reports, run analyses and experiments, surface insights, and drive data-informed decisions and outcomes with product, growth, AI, or partnerships teams.

Embed with a business unit to define problems, design experiments, build metrics and reports, run analyses using SQL/Python, surface actionable insights, and drive data-informed decisions end-to-end.

Embedded on a core business team, own end-to-end analytics: define problems, build metrics/reports, run analyses and experiments, surface insights, and drive data-informed decisions across growth, product, AI, and partnerships.

The Data Scientist will analyze data for risk and trading in Daily Fantasy Sports, develop predictive models, and monitor real-time data.

Develop and maintain predictive pricing, retention, and conversion models using GLMs and advanced analytics; build monitoring tools for rating performance; support rate filings, product pricing analyses, competitor research, and cross-functional collaboration to inform pricing and enterprise risk decisions.

Lead and mentor data science projects using Epic/Cogito and SQL-based tools. Gather requirements, extract and model data, perform statistical analyses, build visualizations and reports, manage stakeholders and project workflows, and standardize team practices and data architecture.

The Data Scientist supports customer use of the Epistemix platform through data integration, modeling, and visualization, improving decision-making and customer satisfaction.

As a Data Scientist, you'll build production-grade ML systems for HVAC efficiency, working on scaling models, database optimization, and real-time monitoring systems.

Lead data science initiatives to develop and deploy AI solutions that improve business outcomes. Collaborate with cross-functional teams to analyze data, create models, and evaluate performance.