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Sports Analytics Machine Learning Jobs in Springfield, OH

Software Engineer, Senior

Dayton, OH ยท On-site +1

$119K - $157K/yr

This is hands-on engineering work - you will be designing and building Python-based software tools that support optical signature modeling, spectral data analysis, and machine learning-enabled sensor ...

... machine learning algorithms, systems analysis, and real-time embedded processor implementation. The Algorithms, Processing and Experimentation (APEX) Group specializes in development of RF/radar ...

... machine learning algorithms, systems analysis, and real-time embedded processor implementation. The Algorithms, Processing and Experimentation (APEX) Group specializes in development of RF/radar ...

Software Engineer, Senior

Dayton, OH ยท On-site +1

$119K - $157K/yr

This is hands-on engineering work -- you will be designing and building Python-based software tools that support optical signature modeling, spectral data analysis, and machine learning-enabled ...

Software Engineer, Senior

Dayton, OH ยท On-site

$119K - $157K/yr

This is hands-on engineering work - you will be designing and building Python-based software tools that support optical signature modeling, spectral data analysis, and machine learning-enabled sensor ...

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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 cities near Springfield, OH are hiring for Sports Analytics Machine Learning jobs? Cities near Springfield, OH with the most Sports Analytics Machine Learning job openings:

Software Engineer, Senior with Security Clearance

GRVTY

Dayton, OH โ€ข On-site

$119K - $157K/yr

Other

Posted 19 days ago


Job description

What Impact You'll Have GRVTY is looking for a Senior Software Engineer to join a small, technically focused team supporting national security missions at a customer site in Dayton, Ohio. This is hands-on engineering work - you will be designing and building Python-based software tools that support optical signature modeling, spectral data analysis, and machine learning-enabled sensor workflows. The work spans algorithm development, data pipeline construction, and integration of ML capabilities into operational and analytical environments. You will work directly with scientists, sensor domain experts, and intelligence analysts - translating complex technical requirements into functional, maintainable software. This is not a role for someone looking to coast. We want someone who is technically sharp, can operate with a degree of autonomy, and understands that the software they build has real downstream impact on mission outcomes. What You'll be Owning * Design, develop, and maintain Python-based software tools supporting optical signature modeling, spectral sensor data processing, and analytical workflows. * Work with sensor physicists, data scientists, and machine learning engineers to translate technical concepts and mission requirements into working software. * Build and optimize data pipelines for ingesting, processing, and analyzing large-scale scientific and sensor datasets. * Develop and integrate machine learning workflows - including training data preparation, model integration, and evaluation - into operational toolsets. * Create clear software architecture documentation, workflow diagrams, and code structure so tools can be maintained, extended, and transitioned effectively. * Test, validate, and troubleshoot algorithms and software modules across development and deployment environments, including classified workspaces. * Manage and maintain Git repositories with discipline - clean commits, meaningful documentation, and reproducible builds. * Contribute to a culture of technical rigor: peer reviews, coding standards, and honest engagement with complex problems. What You Must Have * Active Top Secret clearance with ability to obtain SCI and CI polygraph. * Bachelor's degree in Computer Science, Engineering, Physics, Mathematics, Data Science, or a related STEM field. Equivalent hands-on experience will be considered. * 9+ years of professional software development experience, with demonstrated focus on scientific computing, algorithm development, data processing, or related technical domains or 7+ years of experience and a Masters degree * Expert-level Python programming, including object-oriented design, modular architecture, and production-quality code. * Experience developing software for data-intensive workflows - sensor data, scientific data, simulation, or equivalent. * Ability to work from technical or scientific requirements and produce well-structured software architecture, logic flows, and implementation plans. * Comfortable operating in both Windows and Linux environments, including secure or classified customer workspaces. * Familiarity with source control and development tooling: Git, GitLab, Bitbucket, Jira, Jenkins, or equivalent. * Strong communication skills - able to work directly with domain experts who are not software engineers and translate what they need into software that actually works. What Would be Nice to Have * Experience with optical signature modeling, EO/IR sensor data, spectral analysis, or hyperspectral data processing. * Familiarity with machine learning frameworks and workflows: PyTorch, TensorFlow, scikit-learn, or equivalent. * Experience with scientific Python libraries: NumPy, pandas, OpenCV, SciPy, or similar. * Background in signal processing, image processing, or remote sensing data workflows. * Experience with simulation, modeling, or mission analysis software in a defense or intelligence context. * Familiarity with ML/Ops practices - training pipelines, data labeling, model evaluation, and deployment workflows. * Experience integrating algorithms into existing operational software suites. * Proficiency in a secondary technical language: C, C++, MATLAB, Java, or Rust. * Advanced degree in a relevant technical field (Computer Science, Electrical Engineering, Physics, Image Science, or related). * Prior experience supporting defense, intelligence, or classified customer environments. * Experience with CI/CD practices, automated testing, and DevSecOps tooling.