Lead Applied AI/ML Data Scientist

About Dynatron Dynatron is transforming the automotive service industry with intelligent SaaS solutions that drive measurable results for thousands of dealership service departments. Our analytics, automation, and AI-powered workflows help service leaders improve profitability, increase operational efficiency, and make smarter business decisions. As Dynatron expands its AI capabilities, we're focused on building intelligence that solves meaningful customer problems—not adding AI for its own sake. That requires exceptional applied data science, rigorous evaluation, strong product judgment, and the ability to turn complex automotive data into capabilities that perform reliably in the real world. The Opportunity We're looking for a Lead Applied AI/ML Data Scientist to serve as a technical authority for the AI and machine learning capabilities embedded within Dynatron's SaaS platform. This is a senior, hands-on individual contributor role for someone who has built AI capabilities that reached production, served real customers, and evolved based on what happened after launch. You'll own modeling approaches across core prediction and classification use cases while helping define how Dynatron evaluates, prioritizes, and develops emerging generative AI capabilities. You'll work directly with Product Managers, Product Owners, Engineering, and product leadership to translate business problems into technically sound AI solutions. Just as importantly, you'll help determine which ideas shouldn't be built: challenging assumptions, identifying limitations, and recommending better approaches when the technology doesn't support the desired outcome. Proofs of concept aren't the finish line here. Success means building AI capabilities that create measurable value for customers and perform reliably in production. What You'll Do Lead Applied Machine Learning Own modeling approaches for Dynatron's core classification, prediction, and other applied machine learning use casesDesign features and modeling strategies for complex, messy, real-world automotive dataEstablish rigorous approaches to class imbalance, validation, experimentation, and model evaluationContinuously improve models based on production performance, changing data, and customer outcomesRaise the standard for how applied machine learning is developed, evaluated, documented, and shipped across the organization Build Production AI Capabilities Design and build AI/ML capabilities from initial problem definition through production releaseTranslate customer and product problems into appropriate modeling approaches rather than beginning with a predetermined technologyBuild solutions that balance model quality, scalability, explainability, latency, cost, and maintainabilityRemain engaged after launch to understand real-world performance and improve capabilities based on production evidence Shape the AI Product Roadmap Serve as a technical authority on the feasibility of proposed AI capabilitiesPartner with Product leadership to evaluate opportunities before significant engineering investment is madeClearly articulate what is technically achievable, what requires additional data or sequencing, and what is unlikely to deliver the intended resultRecommend alternative approaches when AI isn't the appropriate solutionHelp prioritize opportunities based on customer value, technical feasibility, data readiness, and implementation complexity Build with Generative AI & Agentic Systems Develop production capabilities using LLMs and modern agentic frameworks where they provide meaningful product valueDesign retrieval architectures, tool-use patterns, and other approaches for grounding AI systems in Dynatron's proprietary dataEvaluate and adapt foundation models for domain-specific applications, including fine-tuning where appropriateEstablish appropriate controls around quality, latency, token usage, and cost per interactionStay current with emerging AI capabilities while applying disciplined judgment about where they belong in production Define AI Evaluation Standards Establish rigorous evaluation methodologies for traditional ML and non-deterministic generative AI systemsDefine appropriate offline and production metrics for individual use casesDesign evaluation frameworks that measure accuracy, reliability, business usefulness, and other relevant quality dimensionsMonitor production performance and use real-world results to guide model improvementHelp establish consistent standards for determining when an AI capability is ready for customers Partner Through Production Work closely with Engineering and MLOps/DevOps partners to establish production-readiness criteriaDefine requirements for deployment, monitoring, retraining, and model lifecycle managementEnsure appropriate handoffs without treating productionization as someone else's problemCollaborate across Data Engineering, Product, and Engineering to ensure AI solutions have the data and infrastructure required to perform reliably What You Bring Applied Data Science & Machine Learning Expertise 10+ years of experience in Data Science, Applied Machine Learning, or a closely related disciplineDeep expertise in traditional machine learning, including classification, feature engineering, class imbalance, and model evaluationSignificant experience working with complex, imperfect real-world datasets rather than exclusively curated research dataStrong understanding of experimental design and how to determine whether a model is actually improving an outcome Production AI Experience — Critical Demonstrated experience shipping AI/ML capabilities into commercial products used by real customersAbility to speak specifically about systems you've built, their scale, how they performed after release, and what you changed based on production evidenceExperience supporting and improving models throughout their production lifecycleStrong understanding of the differences between building a successful prototype and operating a successful AI product Generative AI & LLM Expertise Production experience building with LLMs and agentic frameworksExperience designing retrieval architectures and grounded AI applicationsStrong understanding of evaluation methodologies for non-deterministic systemsExperience managing quality, latency, token consumption, and cost per interaction in productionExperience fine-tuning or otherwise adapting transformer models for domain-specific use cases Product & Business Judgment Demonstrated experience scoping AI initiatives directly with Product Managers and business stakeholdersTrack record of identifying technically weak or commercially impractical AI concepts and influencing stakeholders toward better solutionsAbility to translate business problems into modeling problems—and recognize when the underlying problem doesn't require AIStrong customer orientation with curiosity about the business problem behind the requested capability Technical Skills Expert-level Python and strong SQL skillsComfortable working directly with large datasets in cloud data warehouse environmentsExperience collaborating within modern cloud-based data and ML ecosystemsStrong understanding of the data requirements and dependencies necessary to support production AI Communication & Technical Leadership Ability to communicate sophisticated AI concepts, limitations, and trade-offs clearly to non-technical stakeholdersStrong influence skills and confidence challenging assumptions constructivelyAbility to establish technical standards and raise the quality of work without direct people-management authorityStrong documentation habits and commitment to making technical decisions understandable and reproducible Education Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or another quantitative discipline, or equivalent practical experience Nice to Have Experience working with automotive, dealership, or Fixed Operations dataExperience in another domain involving complex operational records, industry-specific taxonomies, or similarly challenging datasetsExperience with cloud-managed AI/ML services and modern production model lifecycle practicesExperience designing, managing, or governing large-scale expert labeling programsExperience working with proprietary datasets as a foundation for differentiated AI products What Success Looks Like Successful Lead Applied AI/ML Data Scientists at Dynatron: Turn difficult customer problems into AI capabilities that perform reliably in productionRaise the technical standard for classification, prediction, generative AI, and model evaluationHelp Product distinguish compelling AI opportunities from ideas that aren't technically or commercially soundBuild solutions appropriate to the problem rather than defaulting to the newest technologyEstablish clear evidence that AI capabilities work before—and after—they reach customersImprove models based on real-world production performance rather than treating deployment as the finish linePartner effectively with Product, Engineering, Data Engineering, and MLOps from concept through productionUse Dynatron's proprietary automotive data to create differentiated capabilities that deliver measurable customer value Why Dynatron Help shape the AI capabilities at the center of Dynatron's next generation of productsWork with rich, complex automotive datasets that create opportunities for differentiated machine learning and AIInfluence the AI product roadmap as a senior technical authority, not simply execute predefined requirementsBuild across traditional machine learning, generative AI, LLMs, and emerging agentic technologiesHigh-impact Lead IC role with significant technical autonomy and organizational influencePartner directly with Product, Engineering, Data, and technology leadership as Dynatron continues its evolution toward an AI-first organizationRemote-first environment offering autonomy, ownership, and flexibility Compensation & Benefits Base Salary: $180,000/yr Benefits Include: Comprehensive health, dental, and vision insuranceEquity participation through Dynatron's Equity Incentive Plan401(k) with competitive company matchFlexible vacation policy and 11 paid company holidaysEmployer-paid short- and long-term disability and life insuranceHome office setup supportRemote-first working environmentOngoing professional development opportunities Ready to turn complex data and ambitious AI ideas into intelligent products that deliver real customer value? Join Dynatron and help define what production AI looks like across the next generation of automotive software.