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Sports Analytics Machine Learning Jobs in Round Rock, TX

Machine Learning Scientists III Within the AI & Data organization, the Marketplace Science team ... Design experiments and analyses to assess model performance, business outcomes, and marketplace ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

Data analysis and feature engineering: Apply your expertise to identify and generate features that ... Use machine learning and statistical modelling techniques such as Decision Trees, Logistic ...

Senior Data Scientist

Austin, TX · On-site

$200 - $250/hr

Schwab's AI & Data Science organization helps shape the future of client and employee experiences through advanced analytics, machine learning, and generative AI. As a Senior AI & Data Scientist, you ...

Senior Data Scientist

Austin, TX · On-site

$155K - $200K/yr

Schwab's AI & Data Science organization helps shape the future of client and employee experiences through advanced analytics, machine learning, and generative AI. As a Senior AI & Data Scientist, you ...

We are looking for visionary Machine Learning Engineers to join our Applied Group, where you'll ... Excellent problem-solving and analytical skills, with a proactive approach to challenges. * Ability ...

Senior Machine Learning Engineer

Austin, TX · On-site

$121K - $160K/yr

... scientists/analysts, and product managers, to help develop and implement machine learning ... algorithms and testing workflows. Minimum Qualifications Bachelorʼs degree in Computer Science ...

Showing results 21-40

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 Round Rock, TX?

For Sports Analytics Machine Learning jobs in Round Rock, TX, the most frequently searched job titles are:

What job categories do people searching Sports Analytics Machine Learning jobs in Round Rock, TX look for?

The top searched job categories for Sports Analytics Machine Learning jobs in Round Rock, TX are:

What cities near Round Rock, TX are hiring for Sports Analytics Machine Learning jobs?

Cities near Round Rock, TX with the most Sports Analytics Machine Learning job openings:

Machine Learning Engineer, Apple Store Online

Apple Inc.

Austin, TX • On-site

$100 - $125/hr

Other

Re-posted 11 days ago


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 684 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

Machine Learning Engineer, Apple Store Online

Austin, Texas, United States Corporate Functions

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 Machine Learning Engineer. You will lead the way on our Online Retail Decision Automation team by researching and developing the next generation of algorithms used to drive the Apple Online experience! This 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 optimizing Apple‑wide systems & infrastructure. As a member of the fast‑paced team, you will have the outstanding and great opportunity to be part of a new projects and craft upcoming products that will delight and encourage millions of Appleʼs customers every day.

Description

To be successful, you need a strong machine learning background, proven software development skills, a love of learning, and to collaborate with cross‑functional teams, including researchers, engineers, data scientists/analysts, and product managers, to develop and implement machine learning algorithms. You’ll mentor other MLE’s and lead an effort to build scalable end‑to‑end machine learning solutions for our retail customers

Responsibilities
  • Collaborate with other MLEs to build scalable, production‑ready ML solutions, taking algorithms from initial concept through to deployment
  • Contribute 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
Minimum Qualifications
  • Proficiency in one or more object‑oriented programming languages such as Python, Java, C++ and experience building highly scalable distributed systems
  • Hands‑on experience with building data processing pipelines, large scale machine learning systems, and big data technologies (eg: Spark, SQL, Snowflake/Hadoop, etc)
  • Bachelors in a quantitative field, such as Computer Science, Applied Mathematics, Statistics, or Bachelors degree in quantitative field with a focus on AI in coursework
Preferred Qualifications
  • Understanding of machine learning model lifecycle from prototyping, feature engineering, training, inference, deployment, monitoring and continuous improvements via deep analysis)
  • Experience in Recommender Systems, Personalization, Search, Computational Advertising or Natural Language Processing including RAG based Generative AI and transformer architecture
  • 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
  • Skilled in communication, problem solving, strategic thinking

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace.

Learn about reasonable accommodations for job applicants.

Apple accepts applications to this posting on an ongoing basis.

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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