Lead Applied AI/ML Data Scientist

About the role

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 cases

Design features and modeling strategies for complex, messy, real-world automotive data

Establish rigorous approaches to class imbalance, validation, experimentation, and model evaluation

Continuously improve models based on production performance, changing data, and customer outcomes

Raise 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 release

Translate customer and product problems into appropriate modeling approaches rather than beginning with a predetermined technology

Build solutions that balance model quality, scalability, explainability, latency, cost, and maintainability

Remain 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 capabilities

Partner with Product leadership to evaluate opportunities before significant engineering investment is made

Clearly articulate what is technically achievable, what requires additional data or sequencing, and what is unlikely to deliver the intended result

Recommend alternative approaches when AI isn't the appropriate solution

Help 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 value

Design retrieval architectures, tool-use patterns, and other approaches for grounding AI systems in Dynatron's proprietary data

Evaluate and adapt foundation models for domain-specific applications, including fine-tuning where appropriate

Establish appropriate controls around quality, latency, token usage, and cost per interaction

Stay 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 systems

Define appropriate offline and production metrics for individual use cases

Design evaluation frameworks that measure accuracy, reliability, business usefulness, and other relevant quality dimensions

Monitor production performance and use real-world results to guide model improvement

Help 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 criteria

Define requirements for deployment, monitoring, retraining, and model lifecycle management

Ensure appropriate handoffs without treating productionization as someone else's problem

Collaborate 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 discipline

Deep expertise in traditional machine learning, including classification, feature engineering, class imbalance, and model evaluation

Significant experience working with complex, imperfect real-world datasets rather than exclusively curated research data

Strong 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 customers

Ability to speak specifically about systems you've built, their scale, how they performed after release, and what you changed based on production evidence

Experience supporting and improving models throughout their production lifecycle

Strong 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 frameworks

Experience designing retrieval architectures and grounded AI applications

Strong understanding of evaluation methodologies for non-deterministic systems

Experience managing quality, latency, token consumption, and cost per interaction in production

Experience 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 stakeholders

Track record of identifying technically weak or commercially impractical AI concepts and influencing stakeholders toward better solutions

Ability to translate business problems into modeling problems—and recognize when the underlying problem doesn't require AI

Strong customer orientation with curiosity about the business problem behind the requested capability

Technical Skills

Expert-level Python and strong SQL skills

Comfortable working directly with large datasets in cloud data warehouse environments

Experience collaborating within modern cloud-based data and ML ecosystems

Strong 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 stakeholders

Strong influence skills and confidence challenging assumptions constructively

Ability to establish technical standards and raise the quality of work without direct people-management authority

Strong 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 data

Experience in another domain involving complex operational records, industry-specific taxonomies, or similarly challenging datasets

Experience with cloud-managed AI/ML services and modern production model lifecycle practices

Experience designing, managing, or governing large-scale expert labeling programs

Experience 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 production

Raise the technical standard for classification, prediction, generative AI, and model evaluation

Help Product distinguish compelling AI opportunities from ideas that aren't technically or commercially sound

Build solutions appropriate to the problem rather than defaulting to the newest technology

Establish clear evidence that AI capabilities work before—and after—they reach customers

Improve models based on real-world production performance rather than treating deployment as the finish line

Partner effectively with Product, Engineering, Data Engineering, and MLOps from concept through production

Use 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 products

Work with rich, complex automotive datasets that create opportunities for differentiated machine learning and AI

Influence the AI product roadmap as a senior technical authority, not simply execute predefined requirements

Build across traditional machine learning, generative AI, LLMs, and emerging agentic technologies

High-impact Lead IC role with significant technical autonomy and organizational influence

Partner directly with Product, Engineering, Data, and technology leadership as Dynatron continues its evolution toward an AI-first organization

Remote-first environment offering autonomy, ownership, and flexibility

Compensation & Benefits

Base Salary: $180,000/yr

Benefits Include:

Comprehensive health, dental, and vision insurance

Equity participation through Dynatron's Equity Incentive Plan

401(k) with competitive company match

Flexible vacation policy and 11 paid company holidays

Employer-paid short- and long-term disability and life insurance

Home office setup support

Remote-first working environment

Ongoing 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.