Data Scientist

We have an exciting opportunity for a Data Scientist within our data product space. This individual will be focused on designing, building, and deploying machine learning models and data products that support our enterprise initiatives. This role focuses on developing scalable, production ready solutions by translating complex business problems into data-driven approaches and model-based outputs.

Working closely with product managers, engineering teams, and business stakeholders, this position contributes to the development of data products from concept through deployment, ensuring solutions are reliable, performant, and aligned with real world use cases. The role includes hands on model development, feature engineering, and integration into production systems within cloud environments.

The ideal candidate has experience building and operationalizing machine learning models and is comfortable working with modern AI techniques, including large language models (LLMs) and retrieval-augmented generation (RAG), where applicable. Experience with platforms such as Azure, AWS, or similar ecosystems is strongly preferred.

Success in this role requires strong technical expertise, problem-solving skills, and the ability to deliver high-quality solutions within a structured development environment. This role focuses on building and deployment of production data products and is not limited to exploratory analysis or reporting.

This position is open to remote or hybrid.

ESSENTIAL FUNCTIONS & RESPONSIBILITIES:

• Mine and analyze data from internal databases to drive optimization and improvement of product development and business strategies
• Creating new, experimental frameworks to collect data
• Building tools to automate data collection
• Develop custom data models and algorithms to apply to data sets
• Design, build, train, and deploy machine learning models and data products for enterprise use
• Translate business and operational needs into scalable data science solutions and modeling approaches
• Perform feature engineering, data preparation, and exploratory analysis to support model development
• Develop and evaluate models using appropriate techniques (e.g., classification, regression, NLP, optimization)
• Contribute to the design of data products, including model outputs, APIs, and integration into downstream systems
• Support advanced AI use cases, including LLM-based solutions, retrieval-augmented generation (RAG), and hybrid modeling approaches where appropriate
• Collaborate with engineering teams to integrate models into production environments using APIs, pipelines, and cloud services
• Support deployment and lifecycle management of models within Azure Machine Learning, AWS, or similar platforms
• Perform model validation, testing, and documentation to ensure quality and reproducibility
• Contribute to technical design discussions and provide input on architecture and implementation strategies
• Work within the full software development lifecycle (SDLC), including version control, testing, and release processes
• Communicate model behavior, assumptions, and results clearly to technical and non-technical stakeholders
• Develop A/B testing framework and test model quality
• Passion for technology and emerging AI/ML trends
• Additional duties as assigned, Lead research projects that develop and improve data science methodologies and algorithms. Analyze existing solutions, build and test data extraction and transformation architectures, and collaborate with Technology and Product Management on deployment. Investigate production and client data issues, provide data analysis support, maintain SQL, Python, and R code, document processes, and present research findings to internal clients. Top Skills: PythonRSQL Fetch

Senior Data Scientist

2 Days Ago Remote USA Senior level Senior level Big Data * Food * Mobile * Payments Develop and deploy predictive and causal models for personalization, retention, monetization, and product strategy. Design experimentation and measurement frameworks, analyze user and marketing behavior, quantify business impact, and translate complex findings into strategic decisions. Collaborate with Product, Engineering, Marketing, and Data Product teams to build scalable data solutions. Mentor peers, promote rigorous model validation and governance, and apply Python, SQL, Snowflake, dbt, Airflow, Spark, and AWS to production-ready data science initiatives. Top Skills: AirflowAWSBayesian InferenceCausal InferenceCcpaDbtExperimentation FrameworksGdprMachine LearningPythonSnowflakeSparkSQL

What you need to know about the Colorado Tech Scene

With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.

Key Facts About Colorado Tech

• Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
• Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
• Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
• Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
• Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
• Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute

• Strong problem-solving skills with an emphasis on product development.
• Strong foundation in machine learning, statistical modeling, and data science techniques
• Experience building and deploying machine learning models in production environments
• Familiarity with modern AI approaches, including:
• Natural language processing (NLP)
• Large language models (LLMs)
• Retrieval-Augmented Generation (RAG)
• Feature engineering and model evaluation techniques
• Experience working with cloud platforms such as Azure, AWS, or similar ecosystems
• Familiarity with data pipelines, APIs, and integration patterns
• Proficiency in programming languages such as Python and database management including SQL
• Strong problem-solving skills with the ability to structure complex problems into analytical solutions
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.), their real-world advantages/drawbacks and experience with applications
• Excellent presentation and written/verbal communication skills, * Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related technical field; Master’s preferred
• 2-5+ years of experience in data science, machine learning, or related roles
• Experience developing and deploying machine learning models in production environments
• Experience with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or similar
• Exposure to AI platforms such as Azure OpenAI, AWS Bedrock, or similar technologies preferred
• Experience working within enterprise software environments and SDLC practices preferred

Posted Yesterday In-Office or Remote Hiring Remotely in USA 83K-127K Annually Mid level In-Office or Remote Hiring Remotely in USA 83K-127K Annually Mid level Develops and deploys production machine learning models and data products for enterprise use. Responsibilities include data mining, feature engineering, model evaluation, NLP and LLM/RAG solutions, API and pipeline integration, cloud-based deployment, model validation, A/B testing, documentation, and lifecycle management. The role translates business needs into scalable data science solutions and collaborates with product, engineering, and business stakeholders throughout the SDLC. The summary above was generated by AI, CorVel uses a market based approach to pay and our salary ranges may vary depending on your location. Pay rates are established taking into account the following factors: federal, state, and local minimum wage requirements, the geographic location differential, job-related skills, experience, qualifications, internal employee equity, and market conditions. Our ranges may be modified at any time.

For leveled roles (I, II, III, Senior, Lead, etc.) new hires may be slotted into a different level, either up or down, based on assessment during interview process taking into consideration experience, qualifications, and overall fit for the role. The level may impact the salary range and these adjustments would be clarified during the offer process.

Pay Range: $82,574 - $127,490

In general, our opportunities will be posted for up to 1 year from date of posting, or until we have selected candidate(s) to fulfill the opening, whichever comes first.

About CorVel

CorVel, a certified Great Place to Work® Company, is a national provider of industry-leading risk management solutions for the workers’ compensation, auto, health and disability management industries. CorVel was founded in 1987 and has been publicly traded on the NASDAQ stock exchange since 1991. Our continual investment in human capital and technology enable us to deliver the most innovative and integrated solutions to our clients. We are a stable and growing company with a strong, supportive culture and plenty of career advancement opportunities. Over 4,000 people working across the United States embrace our core values of Accountability, Commitment, Excellence, Integrity and Teamwork (ACE-IT!).

A comprehensive benefits package is available for full-time regular employees and includes Medical (HDHP) w/Pharmacy, Dental, Vision, Long Term Disability, Health Savings Account, Flexible Spending Account Options, Life Insurance, Accident Insurance, Critical Illness Insurance, Pre-paid Legal Insurance, Parking and Transit FSA accounts, 401K, ROTH 401K, and paid time off., 83K-133K Annually Mid level 83K-133K Annually Mid level Healthtech * Insurance Designs, validates, and operationalizes predictive, machine learning, and artificial intelligence models using large structured and unstructured datasets. Performs statistical analysis, feature engineering, exploratory analysis, visualization, and clinical program outcome validation. Collaborates cross-functionally to integrate solutions, prepares end-to-end model pipelines, and communicates analytical findings to stakeholders to improve business processes. Top Skills: AWSAzureDatabricksGCPMicrosoft AccessExcelMicrosoft PowerpointMicrosoft WordPower BIPythonRSnowflakeSQL Circana