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Football Data Science Jobs (NOW HIRING)

SumerSports LLC

Senior Deep Learning Engineer

$155K - $185K/yr

... football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia. Our data-driven platform ...

SumerSports LLC

MLOps / ML Platform Engineer

$170K - $200K/yr

... football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia. Our data-driven platform ...

Lorven Technologies

Data Product Owner - Remote

This person would be expected to become the PHS/Football team's subject matter expert on our ... University degree in Computer Science, Mathematics, Engineering or related field. * 8+ years of ...

Swish Analytics

Trading Analyst

San Francisco, CA · On-site +1

$65K/yr

Independently analyze betting trends in a scientific process, turning data into quantifiable ... Passion and intimate knowledge of the NBA, NFL, MLB, NHL, and NCAA Basketball + Football * Strong ...

Swish Analytics

Trading Analyst

San Francisco, CA · Remote

$65K/yr

Independently analyze betting trends in a scientific process, turning data into quantifiable ... Passion and intimate knowledge of the NBA, NFL, MLB, NHL, and NCAA Basketball + Football * Strong ...

SumerSports LLC

Sports Computer Vision Engineer

$165K - $200K/yr

... football fans and NFL clubs. We are a collection of executives, engineers, data scientists, and visionaries from NFL clubs, technology startups, finance, and academia. Our data-driven platform ...

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Football Data Science information

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$205K

How much do football data science jobs pay per year?

As of Sep 4, 2026, the average yearly pay for football data science in the United States is $105,382.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What is a football data science?

A Football Data Science job involves analyzing football-related data to extract insights that can help teams, analysts, and decision-makers improve performance and strategy. This role typically includes working with player tracking data, match statistics, and scouting reports to create predictive models, visualizations, and performance metrics. Professionals in this field use programming languages like Python or R, along with machine learning and statistical techniques, to analyze large datasets. The insights gained can influence tactical decisions, player recruitment, injury prevention, and opposition analysis.

What does a football data scientist do?

A typical day in Football Data Science may involve gathering and cleaning match data, building statistical models to analyze player and team performance, and generating reports or dashboards for coaching staff and management. You might also work on developing predictive metrics, collaborating with scouts to analyze potential recruits, and communicating findings to various stakeholders. Regular meetings with analysts, coaches, and technical teams are common to ensure alignment on objectives and data-driven strategies. This role often balances independent analysis with collaborative teamwork, making it dynamic and closely tied to both match preparation and long-term club strategy.

What are the key skills and qualifications needed to thrive in football data science?

To thrive in Football Data Science, a strong background in statistics, data analysis, and programming (often with a degree in mathematics, computer science, or a related field) is essential. Proficiency with technical tools such as Python, R, SQL, and specialized sports analytics software, as well as relevant certifications or experience with machine learning, is highly valued. Strong communication skills, teamwork, and the ability to present complex findings to non-technical stakeholders help practitioners excel. These abilities enable data scientists to deliver actionable insights for team performance, recruitment, and strategic planning, which are critical to success in this data-driven field.

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What states have the most Football Data Science jobs?

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Football Data Science jobs near you
Infographic showing various Football Data Science job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 86% Physical, 3% Hybrid, and 11% Remote job distribution, with an average salary of $105,382 per year, or $50.7 per hour.

Data Product Analyst - Remote - USA

Lorven Technologies

Remote

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

Role: Data Product Analyst
Location: Remote - USA
Target domain - Retail, CPG, Travel, Hospitality, Sports or gaming
Job description:
Overview
The Data Product Analyst serves as a critical bridge between business stakeholders, analytics teams, and data management groups. This role combines strong data analysis capabilities with core business analysis skills to ensure that data is effectively leveraged to inform strategic decision making, improve processes, and influence solution design. In addition to championing data stewardship, the Data Product Analyst plays a key role in eliciting requirements, documenting business processes, and facilitating alignment across technical and business teams.
Key Responsibilities:
  • Act as the Data Subject Matter Expert to stakeholders with an understanding of data across the end-to-end data supply chain
  • Collect, clean, and analyze data from multiple sources to uncover trends, patterns, and actionable insights.
  • Translate analytical findings into clear, business-friendly insights that support decision-making.
  • Elicit, document, and manage business, functional, and non-functional requirements through techniques such as interviews, workshops, process analysis, and user story creation.
  • Conduct stakeholder analysis to understand needs, roles, dependencies, and expectations across teams.
  • Support prioritization by assessing business value, impacts, complexity, and risk.
  • Ensure traceability of requirements from intake through development, testing, and deployment.
  • Collaborate with data engineering analysts, architects, and engineers to ensure solutions reflect business context and use cases.
  • Define testing acceptance criteria, support user validation, and provide structured feedback for continuous improvement.
  • Monitor and enhance data quality through profiling, validation, remediation, and alignment with organizational priorities.

Key Skills & Competencies
  • Skilled at requirements elicitation, process mapping, and translating business needs into technical specifications.
  • Skilled in crafting user stories, acceptance criteria, and high-quality product and data documentation to support scalable, repeatable workflows.
  • Strong understanding of data stewardship principles, including data quality, lineage, metadata management, and responsible data use and the ability to adapt analytical and stewardship skills across a wide range of NFL use cases.
  • Comfortable connecting data across multiple NFL systems and enriching datasets to enable new insights for football, fan, and business stakeholders.
  • Excellent communication, with the ability to tailor messages for both technical teams (engineering, data science) and business stakeholders (club personnel, league departments).
  • Champions a consumer-first mindset, consistently grounding product, data and insights decisions with a deep understanding of consumer behaviors and needs.
  • Collaborative mindset with the ability to influence without authority and drive alignment across cross-functional teams.
  • Skilled at navigating ambiguity, asking the right clarifying questions, and moving teams toward clarity and action.
  • Naturally curious, with a passion for exploring new data sources, uncovering insights, and improving data quality.
  • Strong critical thinking and structured problem-solving, especially when interpreting incomplete, messy, or evolving datasets.
  • Strong analytical toolkit leveraging SQL, Python, and data querying tools to explore, transform, and validate complex datasets that span across multiple product disciplines.
  • Working knowledge of data modeling, ETL/ELT pipelines, and cloud data platforms (e.g., Snowflake, Databricks, AWS) to support reliable data products.

Qualifications
  • Bachelor's degree in information systems, business analysis, or related fields.
  • 2-5 years of experience in data analysis, business analysis, product analytics, or similar roles.
  • Proven ability to work effectively in cross-functional environments and support the delivery of data products that serve multiple stakeholders.
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About Lorven technologies

Sourced by ZipRecruiter

Lorven Technologies, headquartered in Plainsboro, New Jersey, United States, is a reputable company in the technology industry, specializing in providing effective IT solutions and consulting services. The company's official website, lorventech.com, offers comprehensive insights into its offerings which include but are not limited to software development, IT consulting, project management, and business analysis. Since its inception, Lorven Technologies has been committed to ensuring efficiency and reliability in delivering IT services to its global clientele, establishing itself as a trusted name in the industry.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

2001

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