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Sports Analytics Machine Learning Jobs in Princeton Junction, NJ

Hang

Machine Learning Engineer

New York, NY · On-site +1

This person will implement and develop machine learning models to enhance our platform ... Analyze large datasets to identify trends and patterns, and use this information to inform model ...

Sandbar

Machine Learning Engineer

New York, NY · On-site

$160K - $250K/yr

This also includes utilizing data science and statistical methods to analyze and optimize machine learning model performance across tasks. Lastly, this includes optimizing the aforementioned systems ...

Point72

Machine Learning Engineer

New York, NY · On-site

Role/Responsibilities: We are seeking a Machine Learning Engineer to join the High Frequency ... Excellent analytical skills, with strong attention to detail * Collaborative mindset with strong ...

Point72

Machine Learning Engineer

New York, NY

Role/Responsibilities: We are seeking a Machine Learning Engineer to join the High Frequency ... Excellent analytical skills, with strong attention to detail * Collaborative mindset with strong ...

PhysicsX

Machine Learning Engineer

New York, NY · On-site

Create analytics environments and resources in the cloud or on premise, spanning data engineering ... Experience applying Machine learning methods (including 3D graph/point cloud deep learning methods ...

Spgi

Machine Learning Engineer

New York, NY · On-site +1

$209K - $250K/yr

Machine Learning Engineer Location: 55 Water Street, New York, NY 10041 (Telecommuting permitted ... Conduct original research and data analysis on large proprietary and open-source data sets to ...

Moody's Analytics

Senior DevOps Engineer (Remote)

New York, NY · Remote

$142K - $182K/yr

If you're happy and we can change the ML landscape with our bare hands let's talk about an offer! --- ABOUT MOODY'S ANALYTICS MACHINE LEARNING TEAM We are a team that creates and delivers machine ...

Varsity Tutors

Machine Learning Tutor

Westfield, NJ · 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 cities near Princeton Junction, NJ are hiring for Sports Analytics Machine Learning jobs?

Cities near Princeton Junction, NJ with the most Sports Analytics Machine Learning job openings:

Sports Analytics Machine Learning jobs near you

Machine Learning Engineer

Forhyre

New York, NY

Full-time

Re-posted 25 days ago

Job description

We are looking for a Machine Learning Engineer to help us create artificial intelligence products.


Machine Learning Engineer responsibilities include creating machine learning models and retraining systems. To do this job successfully, you need exceptional skills in statistics and programming. If you also have knowledge of data science and software engineering, we’d like to meet you.


Your ultimate goal will be to shape and build efficient self-learning applications.


Responsibilities


  • Study and transform data science prototypes
  • Design machine learning systems
  • Research and implement appropriate ML algorithms and tools
  • Develop machine learning applications according to requirements
  • Select appropriate datasets and data representation methods
  • Run machine learning tests and experiments
  • Perform statistical analysis and fine-tuning using test results
  • Train and retrain systems when necessary
  • Extend existing ML libraries and frameworks
  • Keep abreast of developments in the field


Requirements


  • Proven experience as a Machine Learning Engineer or similar role
  • Understanding of data structures, data modelling and software architecture
  • Deep knowledge of math, probability, statistics and algorithms
  • Ability to write robust code in Python, Java and R
  • Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
  • Excellent communication skills
  • Ability to work in a team
  • Outstanding analytical and problem-solving skills
  • BSc in Computer Science, Mathematics or similar field; Master’s degree is a plus