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Remote Data Science Sports Jobs in Raleigh, NC (NOW HIRING)

Senior Data Engineer

Raleigh, NC · On-site +1

$103K - $140K/yr

Overview This is a remote role that may only be hired in the following location(s): North Carolina ... Computer Science, Information Systems, Data Science, or related field Preferred Area of Experience ...

Senior Data Engineer

Raleigh, NC · On-site +1

$103K - $140K/yr

Overview This is a remote role that may only be hired in the following location(s): North Carolina ... Computer Science, Information Systems, Data Science, or related field Preferred Area of Experience ...

Senior Data Engineer

Raleigh, NC · On-site +1

$103K - $140K/yr

Overview This is a remote role that may only be hired in the following location(s): North Carolina ... Computer Science, Information Systems, Data Science, or related field Preferred Area of Experience ...

Senior Data Engineer

Raleigh, NC · On-site +1

$103K - $140K/yr

Overview This is a remote role that may only be hired in the following location(s): North Carolina ... Computer Science, Information Systems, Data Science, or related field Preferred Area of Experience ...

Data Engineer

Durham, NC · Remote

$150K/yr

Partner with researchers, data scientists, and technical teams to architect AI and analytics ... remote but needs to sit in one of the following states: AL, AZ, CA, CO, CT, DE, FL, GA, HI, IL, IN ...

New

... remote access to cloud storage platforms like AWS S3, Azure Data Lake Storage, and Google Cloud ... Bachelor's degree or higher, preferably in data science, computer science, or a related ...

Location: Remote in the United States. Reports to: Director, HEOR. Roles and responsibilities ... Deliver fair-balanced, scientifically rigorous presentations on clinical data, real-world evidence ...

Showing results 21-40

Remote Data Science Sports information

What is a remote data science sports job?

A remote data science sports job involves analyzing sports-related data to extract insights, build predictive models, and support decision-making, all while working from a location outside of a traditional office, typically from home. Professionals in this role use statistical methods, programming, and machine learning to evaluate player performance, game strategies, or fan engagement. Their work helps sports teams, leagues, media companies, and betting firms make evidence-based decisions. Remote positions offer flexibility and often require strong communication skills to collaborate with teams virtually. The demand for these roles is growing as the sports industry increasingly relies on data-driven strategies.

What are the key skills and qualifications needed to thrive as a remote data science sports professional?

To thrive as a Remote Data Science Sports professional, you need a strong background in statistics, data analysis, and sports knowledge, often supported by a degree in mathematics, statistics, computer science, or a related field. Familiarity with programming languages such as Python or R, proficiency in data visualization tools, and experience with machine learning frameworks are typically required. Excellent problem-solving abilities, communication skills, and self-motivation are crucial soft skills for collaborating remotely and translating complex data into actionable insights. These skills ensure accurate sports data modeling, effective remote teamwork, and valuable contributions to decision-making in sports organizations.

How do remote data science professionals in the sports industry typically collaborate with coaches and analysts to turn data insights into actionable strategies?

Remote data science professionals in the sports industry often work closely with coaches, analysts, and other stakeholders through regular virtual meetings and collaborative platforms. They translate complex data findings into intuitive visualizations and reports, making it easier for non-technical team members to understand and apply insights. Communication and responsiveness are key, as data scientists may need to quickly adjust analyses based on feedback or new priorities from the sports staff. Building strong relationships and maintaining clear channels of communication help ensure that data-driven recommendations are effectively integrated into training, game strategies, and player development.

What is the difference between Remote Data Science Sports vs Remote Data Analysis Sports?

AspectRemote Data Science SportsRemote Data Analysis Sports
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related fields; programming skills in Python/RBachelor's in Data Analysis, Statistics, or related fields; proficiency in Excel, SQL, and visualization tools
Work EnvironmentCollaborative teams, research-focused, often involves modeling and machine learningData interpretation, reporting, and visualization, often in business contexts
Employer & Industry UsageTech companies, sports analytics firms, media outletsSports teams, media companies, sports analytics agencies

Remote Data Science Sports involves advanced modeling, machine learning, and statistical analysis, requiring higher technical credentials. Remote Data Analysis Sports focuses on interpreting data, creating reports, and visualizations. Both roles are common in sports industry analytics but differ in complexity and technical depth.

Can data science be used in sports?

Data science is widely used in sports to analyze player performance, optimize strategies, and improve team decision-making. Sports data analysts and data scientists utilize tools like machine learning, statistical models, and data visualization to gain insights and enhance athletic outcomes.

Do sports teams hire remote data scientists?

Some sports teams and organizations hire remote data scientists to analyze player performance, game strategies, and fan engagement using data analytics tools. These roles often require skills in statistical modeling, machine learning, and programming languages like Python or R, and may involve collaboration with on-site staff or remote work environments.

How much do remote data science sports make?

Remote data science roles in sports typically have salaries ranging from $70,000 to $130,000 annually, depending on experience, education, and the complexity of projects. Senior positions or those requiring specialized skills in machine learning or sports analytics can earn higher compensation, often exceeding $150,000. These roles often require proficiency in programming languages like Python or R and familiarity with sports data sources and analytics tools.

What are popular job titles related to Remote Data Science Sports jobs in Raleigh, NC?

For Remote Data Science Sports jobs in Raleigh, NC, the most frequently searched job titles are:

What job categories do people searching Remote Data Science Sports jobs in Raleigh, NC look for?

The top searched job categories for Remote Data Science Sports jobs in Raleigh, NC are:

Infographic showing various Remote Data Science Sports job openings in Raleigh, NC as of June 2026, with employment types broken down into 1% Internship, 84% Full Time, 12% Part Time, 1% Temporary, and 2% Contract. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution.

AI Platform Director - Data Engineering

First Citizens Bank

Raleigh, NC • On-site, Remote

$245K/yr

Full-time

Re-posted 18 days ago


Key responsibilities

  • Lead the architecture, development, and operationalization of AI/ML workloads on AWS platforms including SageMaker, Bedrock, Lambda, ECS, EKS, S3, Glue, and Snowflake.

  • Oversee the end-to-end AI lifecycle, including data and model development, deployment, governance, and responsible AI compliance.

  • Partner with data engineering teams to ensure high-quality, governed datasets and define standards for feature engineering, data products, and real-time data integration.


First Citizens Bank rating

7.4

Company rating: 7.4 out of 10

Based on 106 frontline employees who took The Breakroom Quiz

107th of 174 rated banks


Job description

Overview

This is a remote role that may only be hired in the following location(s): North Carolina or Arizona

We are seeking an experienced Director to lead the AI platform engineering and enablement functions within our expanding Cloud Data and AI Platform organization. This role is instrumental in building, operationalizing, and governing the next-generation AI and machine learning ecosystem that powers advanced analytics and responsible AI adoption across the bank. You will own the end-to-end AI lifecycle—from data and model development to MLOps, deployment, governance, and responsible AI compliance in a regulated financial environment.

As a seasoned technology leader, you will bring your expertise in enterprise AI architecture, model operations, and platform engineering to partner with key business, technology, and governance stakeholders—ensuring AI initiatives are responsibly implemented, well-controlled, and deliver measurable value. 


Responsibilities & Qualifications

AWS AI/ML Platform Ownership

  • Architect and lead AI/ML workloads on AWS including:
    • Amazon SageMaker (training, deployment, model registry)
    • AWS Bedrock (foundation models and GenAI use cases)
    • AWS Lambda, ECS, EKS for model serving
    • S3, Glue, Snowflake for data pipelines
  • Define enterprise standards for MLOps, feature stores, and model lifecycle management
  • Build and maintain integrations with enterprise platforms for data ingestion, metadata management, tokenization, and control evidence generation. 
  • Continuously enhance the platform’s automation, resilience, and observability, ensuring robust end-to-end telemetry for both model and data pipelines. 
  • Collaborate with Enterprise Risk, Legal, Compliance, and Model Risk partners to embed Responsible AI principles and audit-ready control evidence directly into platform design. 

Machine Learning & GenAI Execution

  • Oversee development of ML models across all business units including Fraud detection systems, Credit scoring and risk modeling, Customer segmentation and personalization, Liquidity related modeling etc.
  • Lead GenAI initiatives using LLMs for Document intelligence, AI copilots etc.

 

Data & Engineering Collaboration

  • Partner with data engineering teams to ensure high-quality, governed datasets
  • Define feature engineering and data product standards in Snowflake / data lake environments
  • Integrate real-time streaming data for low-latency decision systems

 

Model Governance & Risk Compliance

  • Define and enforce standards, patterns, and guardrails for model deployment, explainability, lineage, and monitoring in alignment with enterprise risk, compliance, and security frameworks. 
  • Partner closely with leaders across Responsible AI Governance, AI Portfolio Management, AI Fluency & Engagement, and Applied Data Science & GenAI, in collaboration with enterprise risk partners, to implement a responsible AI framework that embeds audit-ready control evidence and governance mechanisms directly into the platform’s core design to ensure the platform supports scalable, ethical, compliant, and high-impact AI delivery. 
  • Implement model explainability (SHAP, LIME, interpretability frameworks)
  • Establish responsible AI policies (bias detection, fairness, auditability)

 

Team Building & Leadership

  • Develop and mentor engineering talent, championing Agile practices, continuous learning, and adoption of emerging AI and data engineering technologies. 
  • Mentor senior technical leaders and establish engineering best practices
  • Oversee technical due diligence, onboarding, and management of strategic AI and GenAI vendors and tools, ensuring compatibility with enterprise architecture and control.

Bachelor's Degree and 8 years of experience in Information Technology including application development, support roles, and management.

OR

High School Diploma or GED and 12 years of experience in Information Technology including application development, support roles, and management.

Qualifications

  • Deep hands-on experience building production ML systems on AWS
  • 2+ years in AI/ML, data science, or data engineering leadership roles
  • Strong knowledge of:
    • Machine learning (XGBoost, deep learning, NLP, time series)
    • MLOps practices (CI/CD, model monitoring, drift detection)
    • Distributed systems and cloud architecture
  • Strong programming background in Python + SQL (Scala/Java a plus)
  • Experience working in regulated environments with model governance

Preferred Qualifications

  • Experience with Generative AI / LLM platforms (Bedrock, OpenAI, Claude APIs)
  • Experience in financial services, banking, fintech, or insurance
  • Familiarity with data platforms like Snowflake, Databricks

#LI-JM1


Additional Information

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Qualifications:

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Education:UNAVAILABLEEmployment Type: FULL_TIME

What First Citizens Bank employees say

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Benefits

Hours and flexibility

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