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Sports Analytics Machine Learning Jobs in Dallas, TX

Addison Group

Machine Learning Developer

Dallas, TX · On-site

$115K - $140K/yr

Job Title: Machine Learning Developer Location (city, state): Dallas, Texas - onstie 5x a week ... Strong analytical, organizational, interpersonal, and problem-solving skills. * Ability to work ...

Yum! Brands

Machine Learning Engineer II

Plano, TX · On-site

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting ... Strong analytical and problem-solving skills, with the ability to translate business requirements ...

Addison Group

Machine Learning Developer

Dallas, TX · On-site

$115K - $140K/yr

Job Title: Machine Learning Developer Location (city, state): Dallas, Texas - onstie 5x a week ... Strong analytical, organizational, interpersonal, and problem-solving skills. * Ability to work ...

Varsity Tutors

Machine Learning Tutor

Dallas, TX · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Carrollton, TX · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Grand Prairie, TX · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Plano, TX · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Arlington, TX · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Fort Worth, TX · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Allen, TX · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Varsity Tutors

Machine Learning Tutor

Irving, TX · Remote

$18 - $40/hr

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

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Sports Analytics Machine Learning information

What is sports analytics machine learning?

Sports analytics machine learning is the application of data science and machine learning techniques to analyze sports data, such as player statistics, game outcomes, and biometric information. Professionals in this field develop models to identify patterns, predict player performance, optimize team strategies, and gain competitive advantages. This work involves collecting large datasets, cleaning and processing data, and using algorithms to extract actionable insights that can benefit teams, coaches, and athletes. Sports analytics with machine learning is increasingly used in professional sports to inform decisions about training, recruitment, and game tactics.

How do sports analytics machine learning professionals typically collaborate with coaches and athletes to impact game strategy?

Sports Analytics Machine Learning professionals often work closely with coaches and athletes by translating complex data insights into practical recommendations. They attend strategy meetings, present findings through visualizations, and help interpret trends that can influence training, player selection, and in-game tactics. Effective communication is key, as these professionals must bridge the gap between technical analyses and real-world sports applications. This collaborative environment not only enhances team performance but also provides opportunities to see the direct impact of your work on the field.

What are the key skills and qualifications needed to thrive as a sports analytics machine learning specialist, and why are they important?

To thrive as a Sports Analytics Machine Learning Specialist, you need a strong background in statistics, data analysis, programming (typically in Python or R), and an understanding of machine learning algorithms, often supported by a degree in data science, statistics, or a related field. Familiarity with data visualization tools, sports databases, and machine learning frameworks like TensorFlow or scikit-learn is essential, along with experience using SQL and data pipelines. Strong problem-solving, communication, and collaboration skills help translate complex data findings into actionable insights for coaches, players, and stakeholders. These skills are crucial for extracting meaningful patterns from vast sports datasets and driving performance improvements or strategic decisions within sports organizations.

What are popular job titles related to Sports Analytics Machine Learning jobs in Dallas, TX?

For Sports Analytics Machine Learning jobs in Dallas, TX, the most frequently searched job titles are:

What job categories do people searching Sports Analytics Machine Learning jobs in Dallas, TX look for?

The top searched job categories for Sports Analytics Machine Learning jobs in Dallas, TX are:

What cities near Dallas, TX are hiring for Sports Analytics Machine Learning jobs?

Cities near Dallas, TX with the most Sports Analytics Machine Learning job openings:

Sports Analytics Machine Learning jobs near you
Infographic showing various Sports Analytics Machine Learning job openings in Dallas, TX as of August 2026, with employment types broken down into 82% Full Time, and 18% Part Time. Highlights an 89% In-person, and 11% Hybrid job distribution.

Machine Learning Developer

Addison Group

Dallas, TX • On-site

$115K - $140K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 10 days ago

Job description

Job Title: Machine Learning Developer
Location (city, state): Dallas, Texas - onstie 5x a week
Assignment Type: Direct Hire
Pay: $115,000-$140,000 annually, plus a short-term incentive and long-term incentive.
Benefits: This position is eligible for medical, dental, vision, and 401(k). The company offers fully paid family benefits, a generous 401(k) match, and a competitive paid-time-off program.
Our client is a well-established energy organization with significant operations in the Permian Basin. The company is expanding its artificial intelligence and machine learning capabilities and offers a collaborative environment where employees are trusted to take ownership, contribute ideas, and influence technical direction.
We are seeking a Machine Learning Developer to serve as the first dedicated ML engineering professional within a newly established AI/ML function. This individual will create the MLOps framework, development standards, and platform foundation needed to move machine learning models from experimentation into secure, reliable production environments.
This is a hands-on individual contributor role with significant influence over the organization's future machine learning strategy. The successful candidate will be comfortable setting technical direction, recommending new approaches, and performing the detailed engineering work required to implement those recommendations. This opportunity is ideal for someone who enjoys building programs from the ground up and working in a fast-moving, entrepreneurial environment.
Key Responsibilities:
  • Develop the organization's MLOps strategy, technical standards, reusable workflows, and preferred process for moving models into production.
  • Build and support machine learning solutions within the Databricks environment.
  • Collaborate with data scientists to deploy models using tools such as MLflow, AutoML, Unity Catalog, and Databricks Model Serving.
  • Create automated CI/CD processes for model training, deployment, testing, and promotion between environments.
  • Manage the full model lifecycle, including experiment tracking, model registration, version control, lineage, governance, and user access.
  • Implement monitoring and validation processes for production models, features, and source data.
  • Establish operational visibility for ML systems and assist with troubleshooting and production support when issues arise.
  • Develop standards for data quality, feature reliability, schema validation, and data version management.
  • Produce technical documentation, reference designs, reusable templates, and engineering playbooks.
  • Lead code reviews and share best practices with data science and engineering professionals.
  • Work with business leaders, data scientists, data engineers, and IT teams to define requirements and encourage adoption of shared ML frameworks.
  • Research emerging technologies and recommend enhancements to machine learning delivery, including GenAI, agent-based systems, and AI-assisted development tools.
  • Present technical recommendations to stakeholders and confidently explain or defend a position when viewpoints differ.

Qualifications:
  • Bachelor's degree in computer science, data science, engineering, mathematics, statistics, or a related discipline is required.
  • Three to five years of experience developing, deploying, or supporting machine learning or data-intensive production systems is preferred; candidates with more advanced experience are also encouraged to apply.
  • Hands-on experience with Databricks MLflow and AutoML is required.
  • Advanced Python skills with the ability to create clean, tested, and maintainable production code.
  • Strong SQL capabilities and familiarity with Spark or another distributed data-processing technology.
  • Experience implementing or supporting MLOps practices such as automated pipelines, model deployment, production monitoring, and lifecycle governance.
  • Knowledge of software development fundamentals, including Git, unit testing, CI/CD, and common application design principles.
  • Understanding of widely used machine learning algorithms, model-training methods, evaluation techniques, and hyperparameter tuning.
  • Ability to translate complex technical topics for both technical and nontechnical audiences.
  • Strong analytical, organizational, interpersonal, and problem-solving skills.
  • Ability to work independently, manage competing priorities, and operate with limited supervision.

Apply