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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist/AI Application Solutions Engineer - **Company:** Vision Service Plan - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $84,000 - $142,000 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Business Analytics Applications, Data Analysis, ARM Architecture, Big Data, Software as a Service, Cloud Computing, Cloud Engineering, Software Quality, Cyber Security, Data Governance, Data Infrastructure, Data Visualization, Decision Support Systems, DevOps, Human-Computer Interaction, Python (Programming Language), Machine Learning, Node.Js, Search Technologies, Software Engineering, TypeScript, Cloud Platform System, ReactJS, Large Language Models, Snowflake, Prompt Engineering, Deep Learning, Vector Embeddings, Generative AI, AI Platforms, Information Technology, Performance Monitor, Data Management, Virtual Agents - **Published:** November 11, 2026 - **Apply:** https://www.builtincolorado.com/job/senior-data-scientist-ai-application-solutions-engineer/12176910?handler=ApplyRedirect ## About the Role Bachelor's degree in computer science, data science, statistics, economics, or related functional area; or equivalent experience 6 years of demonstrated experience in any of the following areas: Analytics, Data Science, Machine Learning, AI Platform/Solution Development, Data & AI Engineering, Cloud Platform Engineering or related discipline Flexible and able to change priorities and direction quickly and effectively Excellent written and verbal communication, presentation and analytical skills Strategic skills, business acumen and curiosity to support envisioning work, program planning and strategic partnerships Ability to regularly exercise discretion and independent judgment in the performance of his/her job duties Remain current in the field, including new techniques, approaches, and software available Preferred Skills: * Experience developing and deploying AI, generative AI, and analytics solutions that enable enterprise knowledge discovery, automation, and decision support. * Experience partnering across the full solution lifecycle, including requirements gathering, design, development, testing, implementation, and end-user adoption. * Demonstrated ability to deliver scalable, secure, and maintainable solutions leveraging generative AI, intelligent agents, and advanced analytics technologies. * Proficiency with modern application development technologies such as Python, React, TypeScript, Node.js, APIs, and data visualization frameworks. * Experience designing and implementing AI-enabled solutions using large language models (LLMs), machine learning capabilities, vector embeddings, semantic search, Snowflake Cortex, and other emerging AI technologies. * Experience building and deploying Retrieval-Augmented Generation (RAG) solutions, including document ingestion, data chunking, embeddings, vector databases, retrieval strategies, prompt engineering, and response generation. * Ability to evaluate and optimize AI-generated outputs for accuracy, reliability, performance, security, and overall business value. * Experience utilizing AI-assisted development tools and modern engineering practices to improve productivity while maintaining high standards for code quality, testing, security, and maintainability. * Knowledge of performance monitoring, observability, reliability, scalability, and operational support for AI and analytics solutions in production environments. * Understanding of security, privacy, governance, responsible AI principles, and compliance considerations related to AI and analytics development. * Experience working with cloud-based AI, analytics, and data platforms in enterprise environments. * Strong collaboration and communication skills with the ability to translate business needs into technology solutions. ## Description Develops statistical, machine learning, AI, and predictive solutions to solve complex business problems. Mines and analyzes large datasets, builds algorithms and automated data processes, validates models, and communicates insights to business and product leaders. Designs enterprise AI applications, including generative AI and RAG solutions, while supporting data governance, visualization, security, scalability, monitoring, and responsible AI practices. The summary above was generated by AI Model complex business problems and discovering business insights using statistical, algorithmic, mining, and visualization techniques. The data scientist conducts experiments and methodologies to generate and collect data for business use. Mines available data to identify trends and patterns and generates insights for LOBs and senior leadership Partners with LOBs to identify questions and issues for data analysis and experiments Performs complex statistical analysis on experimental or business data to validate and quantify trends or patterns Constructs predictive models, algorithms, and probability engines to support data analysis or product functions; verifies model and algorithm effectiveness based on real-world results Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers Develops and codes software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources Researches and applies knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions Uses advanced mathematical and statistical concepts and theories to analyze and collect data and construct solutions to business problems Participates in research and implements cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence to make data analysis more efficient and to create new data-driven capabilities and insights Supports user experience specialists and information architects to enhance information visualization through development of dashboards and user interface best practices to analytics and product teams and provides consultations for their data-based experimentations Assists in communicating Enterprise data governance principles throughout the company, Remote or Hybrid United States Mid level Mid level Automotive * Big Data * Information Technology * Robotics * Software * Transportation * Manufacturing Leads aftersales performance across an assigned dealership district by driving revenue, customer retention, customer experience, and KPI achievement. Advises dealer leadership, executes GM customer care and aftersales initiatives, analyzes operational and performance data, develops business plans, improves service lane traffic, and resolves warranty and customer concerns. The role requires frequent territory travel, strong automotive service and parts knowledge, Excel proficiency, and the ability to legally operate a motor vehicle. Top Skills: Excel RapidScale, Manage a portfolio of B2B technology customers, guiding onboarding, adoption, value realization, retention, renewals, and growth. Develop success plans, monitor customer health, conduct business reviews, coordinate cross-functional teams, resolve escalations, and identify risks and expansion opportunities. Maintain account documentation, support continuous improvement, and build trusted customer relationships across managed services, cloud, SaaS, cybersecurity, or hybrid infrastructure environments., Manage a portfolio of B2B technology and managed-services customers, guiding onboarding, adoption, engagement, retention, renewals, and value realization. Develop success plans, monitor customer health, conduct business reviews, coordinate cross-functional teams, resolve escalations, identify growth opportunities, and improve customer success processes. The role requires strong relationship management, organization, communication, and familiarity with cloud technologies and customer success metrics. Top Skills: AWSCRMCustomer Success PlatformsGCPAzureVMware 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