ZipRecruiter

Log In

1

Sports Analytics Machine Learning Jobs in Colorado

Cisco

Principal Machine Learning Engineer

Denver, CO · On-site

The Principal Machine Learning Engineer will define the vision for AI across platforms, lead the ... Log Analytics Expertise - In‑depth knowledge of structured/unstructured system logs, event ...

New

Cymertek

Data Scientist

Aurora, CO

In this role, you will use advanced analytics, machine learning models, and statistical methods to uncover trends, solve complex problems, and support strategic decision-making. Collaborating with ...

Cymertek

Data Scientist

Aurora, CO · On-site

In this role, you will use advanced analytics, machine learning models, and statistical methods to uncover trends, solve complex problems, and support strategic decision-making. Collaborating with ...

Cisco

Principal Machine Learning Engineer

Denver, CO · On-site

$291.50K - $369.10K/yr

Log Analytics Expertise - Indepth knowledge of structured/unstructured system logs, event sequence ... MLOps & Continuous Learning - Fluency in automated retraining, drift detection, incremental updates ...

New

bet365

Python Data Analyst

Denver, CO

$65K - $75K/yr

With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else ... Experience with Google Cloud, BigQuery, financial markets, fintech, Linux and Machine Learning ...

bet365

Python Data Analyst

Denver, CO · On-site

$65K - $75K/yr

With over 750 concurrent sporting fixtures at peak and more live sports streamed than anyone else ... Experience with Google Cloud, BigQuery, financial markets, fintech, Linux and Machine Learning ...

next page

Showing results 1-20

People also search for

All JobsSports Analytics Machine Learning JobsSports Analytics Machine Learning Jobs in Colorado

Sports Analytics Machine Learning information

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.

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 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.
What are popular job titles related to Sports Analytics Machine Learning jobs in Colorado? For Sports Analytics Machine Learning jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Sports Analytics Machine Learning jobs in Colorado look for? The top searched job categories for Sports Analytics Machine Learning jobs in Colorado are:
What cities in Colorado are hiring for Sports Analytics Machine Learning jobs? Cities in Colorado with the most Sports Analytics Machine Learning job openings:
Sports Analytics Machine Learning jobs near you
Principal Machine Learning Engineer

Principal Machine Learning Engineer

Cisco

Denver, CO • On-site

Full-time

Posted 2 days ago

Cisco Systems rating

8.6

Company rating: 8.6 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

16th of 137 rated electronics manufacturers

Job description

Job Summary:
Cisco, through its company Splunk, is building a safer, more resilient digital world with a focus on AI and foundation models. The Principal Machine Learning Engineer will define the vision for AI across platforms, lead the lifecycle of large-scale foundation models, and collaborate with various teams to ensure alignment with organizational objectives.
Responsibilities:
• Set and Drive Vision: Define and champion the strategic vision for AI and foundation models across Splunk and Cisco platforms, shaping the research and technology roadmap to anticipate and address industry‑defining challenges.
• Architect and Lead Breakthroughs: Lead the end‑to‑end lifecycle of research, design, and deployment for large‑scale foundation models targeting machine‑generated data, with deep focus on logs and complementary modalities (time series, traces, events).
• Influence at Scale: Partner with executive leadership, engineering, product, and data science teams to ensure AI solutions align with broader organizational objectives, product strategies, and customer needs.
• Mentorship and Thought Leadership: Cultivate organizational excellence by mentoring senior technical talent, fostering research communities, and driving best practices in AI across global teams.
• Foster Innovation: Embed cutting‑edge research and technological advances into products, driving sustained competitive advantage and transformation at enterprise scale.
Qualifications:
Required:
• PhD in Computer Science, or related quantitative field, plus 7+ years of industry research experience.
• Proven track record in at least one of the following areas: large language modeling for both structure and unstructured data, deep learning‑based time series modeling, advanced anomaly detection, and multi-modality modeling.
• Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow)
• Experience translating research ideas into production systems.
Preferred:
• Deep NLP & Domain‑Adapted LLMs: Background in building and adapting large‑scale language models (e.g., T5, BERT, LLaMA, GPTs) for specialized domains including structured/unstructured logs, text, and event sequences.
• Log Analytics Expertise – In‑depth knowledge of structured/unstructured system logs, event sequence analysis, anomaly detection, and root cause identification.
• Advanced Anomaly Detection – Experience creating robust, scalable approaches (statistical, deep learning, or hybrid) for high‑volume, real‑time logs data.
• Multi‑Modal AI Modeling – Strong track record fusing logs, time series, traces, tabular data, and graphs for foundation models tackling complex operational insights.
• Large‑Scale Training & Optimization – Experience optimizing model architectures, distributed training pipelines, and inference efficiency to minimize cost and latency while preserving accuracy.
• MLOps & Continuous Learning – Fluency in automated retraining, drift detection, incremental updates, and production monitoring of ML models.
• Strong Research Track Record – Publications in top AI/ML conferences or journals (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ACL, KDD) demonstrating contributions to state‑of‑the‑art methods and real‑world applications.
Company:
Cisco develops, manufactures, and sells networking hardware, telecommunications equipment, and other technology services and products. It is a sub-organization of Cisco Press. Founded in 1984, the company is headquartered in San Jose, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Cisco Systems employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Cisco Systems logo

About Cisco Systems

Sourced by ZipRecruiter

Cisco Systems, a global tech titan based in San Jose, CA, US, operates in the information technology and services industry. Founded in 1984, the company was derived from a project between two computer scientists from Stanford University. They aimed to connect different networks of computer systems at the university, resulting in the first multi-protocol router, and subsequently, the birth of Cisco. As an industry-leading manufacturer of networking hardware and telecommunications equipment, Cisco's product and services range includes routers, switches, firewall devices, and telecommunication technology. The company's mission, "to shape the future of the Internet by creating unprecedented value and opportunity for our customers, employees, investors, and ecosystem partners," is a testament to its pursuit of technology-forward innovation and customer satisfaction.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1984

Social media

FacebookTwitter

View All Cisco Systems Jobs

Apply