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Sports Analytics Machine Learning Jobs in Berkeley, CA

S27a

Machine Learning Engineer

San Francisco, CA · On-site

$140 - $210/hr

Perform statistical analysis and apply data mining techniques to diagnose bottlenecks, measure impact, and improve model performance and robustness in production settings. * Deploy machine learning ...

Winaxis

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA (Local) Onsite interview Duration: 12+ Mos H1B Only ... Familiarity with multi-modal data integration and analysis. Strong problem-solving skills and the ...

MM International

Machine Learning Engineer

Fremont, CA · On-site

Machine Learning Engineer Location: Fremont, CA once the documents are verified, a Codility ... Familiarity with multi-modal data integration and analysis. * Strong problem-solving skills and the ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ... and analyzing the results in the wild in order to continuously update and improve accuracy and ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class ... and analyzing the results in the wild in order to continuously update and improve accuracy and ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Hive

Machine Learning Manager

San Francisco, CA · On-site

$180K - $250K/yr

Machine Learning Manager In order to execute our vision, we're constantly growing our machine ... reviewing applications, analyzing resumes, or assessing responses and identifying potential ...

Lyft

Machine Learning Engineer

San Francisco, CA · On-site

Understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning * Experience with translating state-of-the-art ML ...

New

Lyft

Machine Learning Engineer

San Francisco, CA · On-site

Understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learning * Experience with translating state-of-the-art ML ...

New

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All JobsSports Analytics Machine Learning JobsSports Analytics Machine Learning Jobs in Berkeley, CA

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 Berkeley, CA?

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

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

The top searched job categories for Sports Analytics Machine Learning jobs in Berkeley, CA are:

What cities near Berkeley, CA are hiring for Sports Analytics Machine Learning jobs?

Cities near Berkeley, CA 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 Berkeley, CA as of August 2026, with employment types broken down into 82% Full Time, and 18% Part Time. Highlights an 100% In-person job distribution.

Machine Learning Engineer

Happy Elements

San Francisco, CA • On-site

Full-time

Re-posted 15 days ago

Job description

Job Summary:
Happy Elements is a company seeking a Machine Learning Engineer to build, maintain, and improve efficient and reliable data mining and machine learning models. The role involves designing and implementing machine learning models while collaborating closely with data and software engineers to optimize production pipelines.
Responsibilities:
• Build, maintain, and improve efficient and reliable data mining and machine learning models.
• Design, implement and tune machine learning models, and provide performance feedback.
• Work closely with data engineers to adapt and improve data pipelines for production models.
• Work closely with software engineers in putting models into production (interface, SLA, scalability).
Qualifications:
Required:
• Strong academic background required.
• MS in Computer Science or Machine Learning with 2+ years of industry experience or PhD in related field with 1+ years of industry experience required.
• Expert in Python, and computation graph toolkits (e.g., Scikit-learn, Tensorflow).
• Solid experience with Python packages such as Numpy, Panda, and Scikit-learn.
• Expert/Master in common families of machine learning models, feature engineering, feature selection techniques, and tuning of machine learning models.
• Master with SQL or other relational database.
• Master in building and productionizing end-to-end machine learning systems.
• Extensive data modeling and data architecture skills.
• Advanced math skills (linear algebra, Bayesian statistics, group theory).
• Ability to consistently exercise independent discretion and judgment on significant matters.
• Strong analytical, problem-solving and communication skills.
• Ability to work in a team environment
Preferred:
• Knowledge and experience in cloud computing is a plus.
Company:
Happy Elements is focused on the development of social, web, and mobile games as well as publishing services. Founded in 2009, the company is headquartered in Beijing, CHN, with a team of 1001-5000 employees. The company is currently Late Stage.

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