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Sports Analytics Machine Learning Jobs in Michigan

Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data ...

Key ResponsibilitiesUnderstand business requirements and analyze datasets to determine suitable ... J2EE, Logistics, Python, Machine Learning Skills Preferred:AIPGEE, Advance data Migration, API ...

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Stefanini is looking for a Machine Learning Engineer, Dearborn, MI (Onsite) For quick apply, please ... For example, modeling a star schema for a retail analytics platform that supports reporting on ...

Excellent analytical, communication, and problem-solving skills * Ability to work in fast-paced, agile environments Primary Skills: * Python, Machine Learning, Data Science, GCP, BigQuery Experience ...

Senior Machine Learning Engineer Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions ...

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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 cities in Michigan are hiring for Sports Analytics Machine Learning jobs? Cities in Michigan with the most Sports Analytics Machine Learning job openings:
Machine Learning Engineer

Machine Learning Engineer

Stefanini Group

Allen Park, MI

Contractor

Posted 3 days ago


Job description

Stefanini Group is hiring!

Stefanini is looking for a Machine Learning Engineer(Allen Park, MI)

For quick apply, please reach out to Navneet Pathak at 248-213-3677/navneet.pathak@stefanini.com

We are looking for a candidate who is responsible for predicting and/ or extracting meaningful trends/ patterns/ recommendations from raw data, leveraging data science methodologies including Machine Learning (ML), predictive modeling, math, statistics, advanced analytics, etc. 

Key Responsibilities

  • Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making 
  • Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data driven decision-making 
  • Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends 
  • Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation 
  • Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness 

Skills Required:

  • J2EE, Logistics, Python, Machine Learning

Skills Preferred:

  • AIPGEE, Advance data Migration, API, Data Management

Experience Required:

  • 5+ years of experience in relevant field
  • Fully Functional Middleware API: A production-ready middleware layer that ingests, aggregates, and exposes the 6 core operational data points. 
  • Agentic AI Orchestrator: A deployed multi-agent system that autonomously monitors the middleware data, flags anomalies, and generates structured recommendation JSON payloads. 
  • Human-in-the-Loop (HITL) Dashboard Integration: APIs and webhooks that feed the AI's reasoning, recommendations, and confidence scores into our front-end application. 
  • Co-Developed Codebase: A clean, modular, and fully tested Git repository co-authored with our internal team. 
  • Coaching Playbook: A comprehensive training package and transfer-of-ownership document for our internal engineering and product teams

 

Experience Preferred

  • Automotive Supply Chain - Logistics

Education Required

  • Bachelor's Degree

Education Preferred

  • Certification Program

**Listed salary ranges may vary based on experience, qualifications, and local market. Also, some positions may include bonuses or other incentives***

Stefanini takes pride in hiring top talent and developing relationships with our future employees. Our talent acquisition teams will never make an offer of employment without having a phone conversation with you. Those face-to-face conversations will involve a description of the job for which you have applied. We will also speak with you about the process, including interviews and job offers.

About Stefanini Group

The Stefanini Group is a global provider of offshore, onshore and near shore outsourcing, IT digital consulting, systems integration, application, and strategic staffing services to Fortune 1000 enterprises around the world. Our presence is in countries like the Americas, Europe, Africa, and Asia, and more than four hundred clients across a broad spectrum of markets, including financial services, manufacturing, telecommunications, chemical services, technology, public sector, and utilities. Stefanini is a CMM level 5, IT consulting company with a global presence. We are a CMM Level 5 company.

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Education:Bachelor (BA, BS...)Employment Type: CONTRACTOR