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Sports Analytics Machine Learning Jobs in Springfield, OH

Skyline Scientific Inc

Software Engineer, Senior

Dayton, OH · On-site

$114K - $150K/yr

Work with sensor experts, scientists, machine learning specialists, and analysts to translate technical concepts into software requirements, logic trees, schematics, and executable workflows.

Skyline Scientific Inc

Software Engineer, Senior

Dayton, OH · On-site

$114K - $150K/yr

Work with sensor experts, scientists, machine learning specialists, and analysts to translate technical concepts into software requirements, logic trees, schematics, and executable workflows.

GRVTY

Software Engineer, Senior

Dayton, OH · 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 ...

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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:
Sports Analytics Machine Learning jobs near you

Machine Learning Engineer

Radiance Technologies

Beavercreek, OH • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 24 days ago

Job description

Radiance is seeking a Machine Learning Engineer who will advance the artificial intelligence capabilities of the National Air and Space Intelligence Center at Wright Patterson Air Force Base. This engineer will provide expertise in data analytics and algorithm development supporting the integration and analysis of diverse data sources and develop machine learning, data mining and statistical algorithms for pattern recognition and anomaly detection. Additionally, this position will improve upon current methods for the automated processing and exploitation of large data sets. This will include R&D on projects involving the exploitation of data from sensors including investigation of state-of-the-art machine learning classification methods to detect, track, and characterize targets of interest.

Radiance Technologies is an employee-owned company with benefits that are unmatched by most companies in the Dayton OH area. Employee ownership, generous 401K, full health/dental/life/vision insurance benefits, interesting assignments, educational reimbursement, competitive salaries and a pleasant work environment combine to make Radiance Technologies a great place to work and succeed.

Required Experience:

  • A working knowledge of Artificial Neural Networks (ANNs), Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs)

  • Experience in applying core Machine Learning methodologies: Regression, Classification, Clustering, Decision Trees, Dimensional Reduction, Neural Networks & Deep Learning, Feature Engineering

Required Skills & Qualifications:

  • Bachelor's Degree in a quantitative field such as Physics, Engineering, Computer Science, Statistics, or a related field

  • Strong programming skills in at least one of the following languages Python, Matlab, C++

  • Experience with Machine Learning APIs, such as TensorFlow, PyTorch, or Keras

  • Active Secret Clearance with ability to obtain and maintain a TS/SCI

Desired Skills:

  • ML for either natural language processing, computer vision, reinforcement learning, generative modeling, or equivalent experience

  • PhD in data science, mathematics, statistics, computer science, a physical science or engineering is strongly desired

  • A mathematical background (Probability and Statistics)

  • An experienced grasp of version control using Git for nonlinear workflows

  • Thorough understanding of working in research, development and production environments

  • Background in image science, imagery exploitation, spatial analysis, and computer vision are a plus

  • R&D on remotely sensed data to include modeling and development of algorithms.

  • Ability to work independently or in a team environment

  • Strong technical writing and oral communication skills

  • Active Top Secret/SCI clearance

Radiance Technologies is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status.

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