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Sports Analytics Machine Learning Jobs in Seattle, WA

Hive

Senior Machine Learning Engineer

Seattle, WA · On-site

$160K - $250K/yr

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

Hive

Senior Machine Learning Engineer

Seattle, WA · On-site

$160K - $250K/yr

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

Expedia

Machine Learning Scientist III

Seattle, WA · On-site

Our Machine Learning and Data Science team are growing! We are looking to hire researchers and data ... Design and analyze tests to validate your models and quantify their business impact and design ...

Hive

Staff Machine Learning Engineer

Seattle, WA · On-site

$200K - $300K/yr

You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis * You are a subject matter expert in at least one focus area of machine learning, such as ...

Hive

Staff Machine Learning Engineer

Seattle, WA · On-site

$200K - $300K/yr

You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis * You are a subject matter expert in at least one focus area of machine learning, such as ...

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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 are popular job titles related to Sports Analytics Machine Learning jobs in Seattle, WA?

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

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

The top searched job categories for Sports Analytics Machine Learning jobs in Seattle, WA are:

Sports Analytics Machine Learning jobs near you

Senior Machine Learning Engineer

Hive

Seattle, WA • On-site

$160K - $250K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted 26 days ago

Job description

About Hive 

Hive is the leading provider of cloud-based AI solutions to understand, search, and generate content, and is trusted by hundreds of the world's largest and most innovative organizations. The company empowers developers with a portfolio of best-in-class, pre-trained AI models, serving billions of customer API requests every month. Hive also offers turnkey software applications powered by proprietary AI models and datasets, enabling breakthrough use cases across industries. Together, Hive's solutions are transforming content moderation, brand protection, sponsorship measurement, context-based ad targeting, and more.

Hive has raised over $120M in capital from leading investors, including General Catalyst, 8VC, Glynn Capital, Bain & Company, Visa Ventures, and others. We have over 250 employees globally in our San Francisco, Seattle, and Delhi offices. Please reach out if you are interested in joining the future of AI!

Senior Machine Learning Engineer

In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the forefront of deep learning technology, prototyping state-of-the-art neural net models and launching these models into production. We value hard workers who have no qualms working with terabyte-scale datasets, who are interested in learning new technologies at all levels of the machine learning stack, and who move fast and take ownership of their projects. Our ideal candidate has experience creating a working machine learning-powered project from the ground up, contributes innovative ideas and ingenious implementations to the team, and is capable of planning out scalable, maintainable data pipelines.
Responsibilities
  • Everything involved in applying a ML model to a production use case, including, designing and coding up the neural network, gathering and refining data, training and tuning the model, deploying it at scale with high throughput and uptime, and analyzing the results in the wild in order to continuously update and improve accuracy and speed
  • Write and maintain scalable, performant and secure code that can be shared across platforms
  • Meaningfully contribute to the product and core backend systems by suggesting and executing improvements
  • Improve engineering standards, tooling, processes and security
  • Develop novel, accurate, and performant ML algorithms for use at scale
  • Conduct metric-driven research experiments to improve model performance
  • Provide mentorship to and help onboard junior ML engineers
  • Collaborate cross-functionally with other teams
  • Utilize OWASP top 10 techniques to secure code from vulnerabilities
  • Maintain awareness of industry best practices for data maintenance handling as it relates to your role
  • Adhere to policies, guidelines and procedures pertaining to the protection of information assets
  • Report actual or suspected security and/or policy violations/breaches to an appropriate authority
Requirements
  • You have a Bachelor's Degree in computer science or a related field
  • You have a minimum of 5 years of building production scale ML models
  • You know the ins and outs modern machine learning frameworks, such as PyTorch or Tensorflow
  • You are an expert in scripting languages such as Python and/or shell scripts, particularly for data analysis
  • You have experience writing code and training across distributed systems
  • You have an ability to understand and make well-reasoned tradeoffs in designing features
  • You can lead end to end development of new products
  • You are very knowledgeable in at least one focus area of machine learning, such as computer vision or NLP
  • You strongly believe in high code quality, automated testing, and other engineering best practices
  • You have attention to detail and a passion for correctness
  • You are comfortable with ambiguity and scoping solutions with your teammates
  • You have strong interpersonal and communication skills with a bias towards action
Who We Are

We are a group of ambitious individuals who are passionate about creating a revolutionary AI company. At Hive, you will have a steep learning curve and an opportunity to contribute to one of the fastest growing AI start-ups in San Francisco. The work you do here will have a noticeable and direct impact on the development of the company.

Thank you for your interest in Hive and we hope to meet you soon!

The current expected base salary for this position ranges from $160,000 - $250,000. Actual compensation may vary depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the total compensation package that is provided to compensate and recognize employees for their work; stock options may be offered in addition to the range provided here.

Employees are eligible to participate in a number of Company-sponsored benefits, including health, vision and dental insurance. Employees are also eligible to participate in a gym membership as part of our commitment to employee wellness. In addition, employees will be entitled to paid vacation in accordance with the Company's vacation policy.

Hired applicant may receive an equity grant in the form of an option to purchase stock in the future for a specified price.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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