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Sports Analytics Machine Learning Jobs in Concord, 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 ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

Contribute to the development and application of advanced analysis methodologies; analyze data ... Master's degree in Machine Learning, Computational Biology, Statistics, Computer Science ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

$9.7K/wk

Contribute to the development and application of advanced analysis methodologies; analyze data ... Master's degree in Machine Learning, Computational Biology, Statistics, Computer Science ...

Hive

Machine Learning Engineer

San Francisco, CA

$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

$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 ...

LLNL

Machine Learning Researcher

Livermore, CA

We have an opening for a Machine Learning and Data Analysis expert to join our team and advance the discipline as well as apply cutting edge tools and techniques to some of society's most important ...

LLNL

Machine Learning Researcher

Livermore, CA · On-site

$9.8K/wk

We have an opening for a Machine Learning and Data Analysis expert to join our team and advance the discipline as well as apply cutting edge tools and techniques to some of society's most important ...

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

LLNL

Machine Learning Researcher

Livermore, CA · On-site

We have an opening for a Machine Learning and Data Analysis expert to join our team and advance the discipline as well as apply cutting edge tools and techniques to some of society's most important ...

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

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

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

Cities near Concord, 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 Concord, 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

S27a

San Francisco, CA • On-site

$140 - $210/hr

Other

Posted 21 days ago

Job description

Responsible for developing next-generation AI systems designed to simplify task automation for users. This role involves designing, evaluating, deploying, and maintaining AI solutions, utilizing both Large Language Models (LLMs) and Bardeen's custom models in areas such as semantic parsing, dialog systems, agents, and text generation. The position collaborates with engineers to integrate AI features into Bardeen's products, ensuring a high-quality user experience.

Specific duties include:

  • Research, design, and implement machine learning algorithms to optimize workflow automation.

  • Develop, test, and modify computer programs to apply machine learning models to real-world applications.

  • Research, design, and implement machine learning and AI algorithms to model real world processes, including process discovery, process conformance, and opportunity identification for automation and AI agents.

  • Develop, test, and modify computer programs that apply machine learning models to operational data sources such as event logs, clickstreams, tickets, documents, and call transcripts.

  • Design and improve methods for process and entity extraction from unstructured and semi structured data, including tasks, systems, stakeholders, and key business objects.

  • Stay familiar with and evaluate state of the art research in process mining, workflow intelligence, representation learning for events and processes, and LLM based planning and tool use, and translate it into practical enterprise solutions.

  • 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 models into production systems, ensuring scalability and efficiency.

  • Maintain, monitor, and enhance deployed machine learning systems to ensure continuous improvement.

  • Collaborate with software engineers, data scientists, and product teams to integrate AI solutions.

  • Prepare technical documentation and reports detailing methodologies and outcomes.

  • Utilize cloud computing platforms such as AWS and GCP to manage large-scale data processing and storage.

  • Ensure compliance with industry standards, data governance, and security protocols for machine learning applications.

Job Requirements:

Requires a Master's degree in Computational Science and Engineering, or a closely related field that focuses on Machine Learning, and 1 year of experience.

Experience must include:

  • Experience with modern deep learning models, particularly large language models (LLMs) and multimodal architectures used for understanding text, structured data, and behavioral traces.

  • Familiarity with OpenAI, Anthropic, or Hugging Face Transformers (GPT, Mistral, LLaMA, etc.).

  • Experience with Python, Hugging Face, and OpenAI, Gemini and Anthropic SDKs.

  • Experience with designing evaluation frameworks, benchmarking model variants, and measuring before/after impact.

  • Experience with production-grade data and inference infrastructure, including AWS and GCP.

  • Experience with monitoring, optimization, and scaling of LLM inference workloads across distributed systems.

  • Experience with ML and AI algorithms to model real world business processes and identification of high impact automation and AI agent opportunities.

  • Experience with using LLMs for performing statistical analysis.

Remote work is permitted. Travel is required to unanticipated locations nationwide. Travel is less than 5% of time.

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