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Sports Analytics Machine Learning Jobs in Austin, TX

... scientists/analysts, and product managers, to help develop and implement machine learning ... algorithms and testing workflows.","responsibilities":"Collaborate with other MLEs to build ...

... scientists/analysts, and product managers, to help develop and implement machine learning ... algorithms and testing workflows.","responsibilities":"Collaborate with other MLEs to build ...

... scientists/analysts, and product managers, to help develop and implement machine learning ... algorithms and testing workflows.","responsibilities":"Collaborate with other MLEs to build ...

Work on algorithm analysis, performance analysis and architecture definition of Machine Learning ASICs * Map Data Center workloads to heterogeneous ASICs that contain multiple different programmable ...

New

Developing and applying analytics, machine learning, and data science techniques to cyber use cases across security operations, threat detection, and incident response * Working with technologies ...

Developing and applying analytics, machine learning, and data science techniques to cyber use cases across security operations, threat detection, and incident response * Working with technologies ...

Showing results 41-60

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 Austin, TX? For Sports Analytics Machine Learning jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Sports Analytics Machine Learning jobs in Austin, TX look for? The top searched job categories for Sports Analytics Machine Learning jobs in Austin, TX are:
What cities near Austin, TX are hiring for Sports Analytics Machine Learning jobs? Cities near Austin, TX with the most Sports Analytics Machine Learning job openings:

Senior Machine Learning Engineer

Apple

Austin, TX

$184K - $324K/yr

Full-time

Medical, Dental, Retirement

Re-posted yesterday


Apple rating

8.0

Company rating: 8.0 out of 10

Based on 677 frontline employees who took The Breakroom Quiz

7th of 30 rated technology retailers


Job description

Imagine what you could do here! The people here at Apple don’t just create products - they build the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to foster a culture where everyone belongs and is inspired to do their best work.
Here on the Apple Store Online team, we are responsible for Apple’s largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things.
We are looking for a passionate, highly motivated, and hands-on applied Senior Machine Learning Engineer. This role will assist our Online Retail Decision Automation team by helping to research and develop the next generation of algorithms used to drive the Apple Online experience! The role spans central areas of our Apple Online Store including developing models for product search, recommendation systems (e.g. ranking, page generation), personalization (e.g. evidence, messaging, marketing), Generative AI and optimize Apple-wide systems & infrastructure. As a member of the fast-paced team, you will have the outstanding and great opportunity to work on new projects and craft upcoming products that will delight and encourage millions of Appleʼs customers ever day.
Description
To be successful, candidates will need a machine learning background, proven software development skills, a love of learning. They will also need to be able to collaborate with multi-functional teams, including researchers, engineers, data scientists/analysts, and product managers, to help develop and implement machine learning algorithms and testing workflows.","responsibilities":"Collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment.
Give to the ongoing improvement of our ML infrastructure and tooling.
Engage in continuous learning and development, staying up-to-date with the latest advances in machine learning and software engineering.
Mentor junior MLEs on the team to ensure best practices are followed.
Preferred Qualifications
PhD or Graduate degree with research/work experience using data science techniques (including but not limited to Computer Science, Statistics, Mathematics, etc).
Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture.
Skilled in communication, problem solving, critical thinking.
Experience using Deep Learning, Bandits, Probabilistic Graphical Models, or Reinforcement Learning in real applications a plus.
Experience with Spark, TensorFlow, Keras, and PyTorch a plus
Minimum Qualifications
Bachelorʼs degree in Computer Science, Statistics, Mathematics with equivalent experience.
5+ years of related experience building high throughput scalable applications or building machine learning models.
Proficiency in one or more object-oriented programming languages such as Python, Java, C++ and experience building distributed systems.
Experience building data processing pipelines and large scale machine learning systems with experience in big data technologies like Spark, SQL, Snowflake/Hadoop, etc.
Skilled in communication, problem solving, critical thinking Attention to detail, data accuracy and quality of output.
Pay & Benefits
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976