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Remote Applied Data Analytics Jobs in Dallas, TX

YO AI Labs

AI Data Scientist - Remote

Dallas, TX · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

New

YO AI Labs

AI Data Scientist Expert - Remote

Dallas, TX · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

YO AI Labs

AI Data Science Expert - Remote

Dallas, TX · Remote

$100 - $200/hr

Remote Job Overview We are seeking experienced AI Data Science Domain Experts to contribute their ... Applied AI, Statistics, Quantitative Analytics, or Data Analytics. * Experience producing or ...

SmartLight Analytics

Senior Data Analyst

Plano, TX · On-site +1

$80K - $101K/yr

This position is a remote position. Key Responsibilities: Data Analysis and Interpretation * Develop a deep understanding of the organization's key initiatives and provide analytical solutions that ...

SmartLight Analytics

Senior Data Analyst

Plano, TX · Remote

$88K - $111K/yr

This position is a remote position. Key Responsibilities: Data Analysis and Interpretation * Develop a deep understanding of the organization's key initiatives and provide analytical solutions that ...

USAA

Director, Business and Data Analytics

Plano, TX · On-site +1

USAA roles may offer remote or hybrid flexibility for active-duty military spouses consistent with ... The Opportunity As a dedicated Director, Business and Data Analytics for the Voice of Member ...

Workiva

Spring 2027 Intern - Data Analytics

Dallas, TX · On-site +1

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

Workiva

Spring 2027 Intern - Data Analytics

Mckinney, TX · On-site +1

$22/hr

Analyze data to drive decision-making on new features of Wdesk * Suggest new product development ... This internship is primarily a remote opportunity. However, if you are located near one of our ...

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All JobsApplied Data Analytics JobsRemote Applied Data Analytics JobsRemote Applied Data Analytics Jobs in Dallas, TX

Remote Applied Data Analytics information

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How much do remote applied data analytics jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for remote applied data analytics in Dallas, TX is $54.16, according to ZipRecruiter salary data. Most workers in this role earn between $43.51 and $61.35 per hour, depending on experience, location, and employer.

What is remote applied data analytics?

A Remote Applied Data Analytics job involves analyzing data to extract insights and help organizations make data-driven decisions, all while working from a location outside of a traditional office. Professionals in this role use statistical methods, programming, and data visualization tools to interpret complex datasets. They often collaborate with cross-functional teams to solve business problems, optimize processes, and present actionable findings. Remote positions in this field require strong technical skills, good communication, and the ability to work independently using digital collaboration tools.

What are the key skills and qualifications needed to thrive as a remote applied data analytics professional?

To thrive as a Remote Applied Data Analytics professional, you need a strong background in statistics, data analysis, and problem-solving, typically supported by a degree in a quantitative field. Proficiency with data analytics tools such as Python, R, SQL, and visualization platforms like Tableau or Power BI, as well as familiarity with data management systems, is essential. Strong communication, self-motivation, and the ability to work independently are key soft skills for succeeding remotely and translating data insights into actionable recommendations. These skills ensure effective analysis, clear communication of findings, and the ability to drive data-informed decisions in a remote work environment.

What are some common challenges faced by professionals in remote applied data analytics roles, and how can they be addressed?

Remote applied data analytics professionals often encounter challenges such as effective communication with cross-functional teams, maintaining data security, and managing time across different time zones. To address these issues, it's important to leverage collaborative tools for clear communication, establish regular check-ins, and follow best practices for data privacy. Additionally, setting structured work hours and proactively aligning with teammates can help ensure smooth project workflows and successful outcomes.

What is the difference between Remote Applied Data Analytics vs Remote Data Analyst?

AspectRemote Applied Data AnalyticsRemote Data Analyst
Required CredentialsBachelor's in Data Science, Analytics, or related field; proficiency in analytics toolsBachelor's in Statistics, Mathematics, or related field; experience with data visualization tools
Work EnvironmentCollaborative teams, project-based tasks, often cross-functionalData-focused tasks, reporting, and data interpretation within organizations
Employer & Industry UsageTech, finance, healthcare, consulting firmsBusiness, marketing, finance, and healthcare sectors

Remote Applied Data Analytics involves applying advanced analytics techniques to solve complex problems, often requiring knowledge of data science tools. Remote Data Analysts focus on interpreting data, creating reports, and supporting decision-making. While both roles require analytical skills, Applied Data Analytics emphasizes modeling and predictive analytics, whereas Data Analysts concentrate on data interpretation and visualization.

What are popular job titles related to Remote Applied Data Analytics jobs in Dallas, TX?

For Remote Applied Data Analytics jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Remote Applied Data Analytics jobs in Dallas, TX look for?

The top searched job categories for Remote Applied Data Analytics jobs in Dallas, TX are:

Remote Applied Data Analytics jobs near you
Infographic showing various Remote Applied Data Analytics job openings in Dallas, TX as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 81% Full Time, 13% Part Time, and 4% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $112,647 per year, or $54.2 per hour.

Lead Applied AI/ML Data Scientist

Richardson, TX • On-site, Remote

Dynatron Software
Software Development • 51 - 200 employees
Learn more about Dynatron Softwareexternal

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago

Job description

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.

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