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Sports Analytics Machine Learning Jobs in Raleigh, NC

Berriehill Research

Senior AI Technologist

Raleigh, NC · On-site +1

$48.75 - $63/hr

Experience preparing and transforming data for analytics, machine learning, search, or AI-enabled applications. * Experience designing vector databases and retrieval pipelines. * Experience ...

ARA

Senior AI Technologist

Raleigh, NC · On-site

$48.75 - $63/hr

Experience preparing and transforming data for analytics, machine learning, search, or AI-enabled applications. * Experience designing vector databases and retrieval pipelines. * Experience ...

Labcorp

Associate Data Scientist

Durham, NC · Hybrid

$57K - $57K/yr

As an Associate Data Scientist , you will join a collaborative team dedicated to solving complex problems using advanced analytics, machine learning, and data-driven insights. This is an exciting ...

Labcorp

Associate Data Scientist

Durham, NC · On-site

$57K - $57K/yr

As an Associate Data Scientist , you will join a collaborative team dedicated to solving complex problems using advanced analytics, machine learning, and data-driven insights. This is an exciting ...

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site +1

Data Analysis and Modeling : Oversee advanced data analysis, modeling, and machine learning to develop predictive and prescriptive models that drive business outcomes. * Data Collection and ...

LexisNexis

Director, Data Sciences

Raleigh, NC · On-site

Data Analysis and Modeling : Oversee advanced data analysis, modeling, and machine learning to develop predictive and prescriptive models that drive business outcomes. * Data Collection and ...

Truist

Data Scientist II

Raleigh, NC

English (Required) Work Shift: 1st shift (United States of America) Please review the following Perform sophisticated analytics (statistical and predictive analytics, machine learning modeling, etc ...

Pentair

Data Architect

Apex, NC · On-site

$110K - $205K/yr

Build the Foundation for Analytics & AI * Develop data structures that support robust reporting, dashboards, and KPI frameworks. * Prepare the environment for machine learning initiatives, including ...

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

Senior AI Technologist

Berriehill Research

Raleigh, NC • On-site, Remote

$48.75 - $63/hr

Full-time

Posted 28 days ago

Key responsibilities

  • Identify, evaluate, and prioritize opportunities to integrate AI into organizational processes and tooling.

  • Design and implement data structures, metadata models, naming conventions, and data standards to support AI initiatives.

  • Build and maintain data preparation pipelines to support model training, testing, retrieval, and operational AI applications.

Job description

Essential Functions:

  • Identify, evaluate, and prioritize opportunities to integrate AI into existing and new organizational processes and tooling.
  • Design and implement data structures, metadata models, naming conventions, and data standards to support AI and machine learning initiatives.
  • Support onboarding new AI projects by identifying data requirements, assessing data readiness, and defining ingestion and preparation workflows.
  • Develop processes to measure and improve ongoing data quality, consistency, completeness, and accuracy across AI datasets and workflows.
  • Build and maintain data preparation pipelines to support model training, testing, retrieval, and operational AI applications.
  • Collaborate with technical and business stakeholders across divisions to understand data sources, use cases, and operational constraints.
  • Create and maintain documentation for data standards, transformation logic, onboarding procedures, and quality controls.
  • Partner with AI, software, platform, and security teams to ensure data workflows are scalable, secure, and aligned with organizational objectives.

Experience and Skills Required:

  • Bachelor’s degree in computer science, Data Engineering, Information Systems, Engineering, Mathematics, or a related STEM field 8-10 years of engineering experience
  • 3+ years of experience supporting AI, natural language processing, RAG, and related solutions.
  • Experience preparing and transforming data for analytics, machine learning, search, or AI-enabled applications.
  • Experience designing vector databases and retrieval pipelines.
  • Experience developing MCP Servers and Clients.
  • Understanding of data quality management practices, including validation, normalization, deduplication, and error handling.
  • Experience working with AI platforms, Kubernetes, and cloud AI environments (Azure Foundry, AWS Bedrock).
  • Strong experience developing AI solutions in Python, Golang, or Typescript.
  • Strong analytical, troubleshooting, and documentation skills.

Preferred:

  • Experience with data platforms and tooling such as Pandas, Spark, Airflow, dbt, or similar ecosystems.
  • Familiarity with vector databases, embeddings pipelines, chunking strategies, and retrieval-augmented generation workflows.
  • Experience designing data schemas, taxonomies, ontologies, or metadata standards for enterprise information.
  • Experience working in regulated environments with standards such as NIST or CMMC.
  • Experience supporting scientific, engineering, defense, or national security-related data initiatives.
  • Experience working with DevOps systems, git, CI/CD, GitOps.
  • DoD experience.
  • Active Secret clearance preferred, or ability to obtain and maintain a Secret clearance.

Education:

  • Bachelor’s degree in CS, Software Engineering or other IT-related field or equivalent experience

REMOTE WORK NOTICE: This position may be performed fully remote, hybrid, or onsite at an ARA office. Preference will be given to candidates located onsite in the Albuquerque, NM and Raleigh, NC area.

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