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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Data and AI Scientist - **Company:** Pemco, Ltd. - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $138,000.0 - $260,000.0 - **Contract:** Permanent contract - **Skills:** Unity 3d, Agile Methodology, Artificial Intelligence, Microsoft Azure, Cloud Engineering, Software Quality, Information Engineering, Fraud Prevention and Detection, Graph Database, Python (Programming Language), Machine Learning, Natural Language Processing, Scrum Methodology, Azure Machine Learning, Software Engineering, SQL Databases, Feature Engineering, Azure Data Factory, Large Language Models, Snowflake, Deep Learning, Model Validation, Generative AI, Data Lakes, Pyspark, Information Technology, HuggingFace, Xgboost, Performance Monitor, Machine Learning Operations, Azure Synapse Analytics, Unsupervised Learning, Databricks - **Published:** September 5, 2026 - **Apply:** https://www.builtincolorado.com/job/principal-data-and-ai-scientist/11017290?handler=ApplyRedirect ## About the Role * B.A. or B.S. degree or equivalent work experience in a related field, such as Computer Science, Software Engineering, Artificial Intelligence, Machine Learning, Data Science, or Data Engineering. * Master's degree or Ph.D. in a related field, such as Artificial Intelligence, Data Science, or Machine Learning preferred. * 10 years of enterprise-scale experience in designing, implementing, and deploying AI/ML models. * 7 years of experience working with cloud-based AI platforms, including Azure Machine Learning, Databricks, and Snowflake. * 7 years of experience in implementing both supervised and unsupervised learning techniques in real-world applications. * Experience in the insurance industry, particularly in Auto, Home, and Umbrella insurance processes, underwriting, claims analysis, and risk assessment is required. * Experience working with advanced AI frameworks such as LangChain, LlamaIndex, and Hugging Face transformers is preferred. * Hands-on experience with Gen AI, RAG pipelines, Vector Databases, and Knowledge Graphs. * Strong problem-solving skills and a deep understanding of statistical and mathematical principles. * Strong experience in natural language processing (NLP) and generative AI applications. * Expertise in MLOps, model lifecycle management, and AI model deployment at scale. * Proficient in Python, PySpark, and SQL. * Deep understanding of Azure Databricks, Delta Lake, Unity Catalog, Azure Synapse Analytics, and Azure Data Factory. * Experience with distributed model training and serving on Databricks * Familiarity with Azure OpenAI, LLM fine-tuning, or cognitive services is preferred. * Expertise in both supervised and unsupervised learning techniques and the ability to implement AI/ML solutions that enhance data-driven decision-making in the insurance industry, particularly in Auto, Home, and Umbrella insurance. * Familiarity with agile software delivery methodologies such as Scrum. ## Description We are seeking a Principal Data Scientist to lead the design, development, and deployment of advanced analytics and machine learning solutions across our insurance portfolio. This is a hands-on technical leadership role for an experienced data scientist who can translate ambiguous business problems into scalable, production-ready models that drive measurable impact. As a Principal Data Scientist, you will operate as a trusted technical advisor to senior leadership, set modeling and experimentation standards, mentor senior and staff-level data scientists, and influence the company's long-term data and AI strategy. What You'll Be Doing: Technical Leadership & Modeling * Lead the development of advanced statistical and machine learning models across core insurance domains such as: + Pricing and rating + Underwriting and risk selection + Claims severity, frequency, and fraud detection + Customer lifetime value, retention, and growth * Design end-to-end analytical solutions, from problem formulation and feature engineering to model deployment and monitoring. * Champion best practices in model validation, explainability, fairness, and performance monitoring, aligned with regulatory and ethical standards. * Evaluate and select appropriate modeling techniques (e.g., GLMs, gradient boosting, deep learning, survival analysis, Bayesian methods) based on business context. Strategic Influence * Partner with executives, product leaders, and actuarial teams to shape analytics strategy and identify high-impact opportunities. * Translate complex analytical findings into clear, actionable insights for both technical and nontechnical audiences. * Influence roadmap decisions by quantifying business impact, risk, and uncertainty. Platform & Production Excellence * Collaborate closely with data engineering and ML platform teams to ensure models are productionized effectively and maintained at scale. * Define and promote standards for model reproducibility, documentation, testing, and lifecycle management. * Contribute to the evolution of internal data science tooling, experimentation frameworks, and ML infrastructure. Mentorship & Culture * Serve as a technical mentor and role model for emerging data scientists. * Raise the bar for analytical rigor, code quality, and scientific thinking across the organization. * Foster a culture of curiosity, experimentation, and evidence-based decision-making. * Demonstrate behaviors consistent with PEMCO's policies, values, code of ethics, and business conduct. * Authentically support the PEMCO Brand and constantly are on the lookout for top talent to join us to achieve our Mission to Worry Less and Live More. * Other duties as assigned. ## Related Videos - [Inside the AI Revolution: How Microsoft is Empowering the World to Achieve More](https://www.wearedevelopers.com/videos/869-inside-the-ai-revolution-how-microsoft-is-empowering-the-world-to-achieve-more) - [Reality and Beyond: Coding a Drone Using {Unity 3D .NET} and ChatGPT AI!](https://www.wearedevelopers.com/videos/702-reality-and-beyond-coding-a-drone-using-unity-3d-net-and-chatgpt-ai) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Pioneering AI Assistants in Banking](https://www.wearedevelopers.com/videos/1627-pioneering-ai-assistants-in-banking) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)