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Non Union Football Data Analytics Jobs (NOW HIRING)

SumerSports LLC

Sr. Football Data Scientist

Build and implement analytical football models, providing valuable insights to enhance our football analytics offerings. Conduct comprehensive data analysis to extract actionable insights. * Model ...

Swish Analytics

Sports Data Analyst

San Francisco, CA · On-site +1

Deep knowledge of a second sport including football, basketball, baseball, hockey or tennis * Exposure to the data science process and tech stack * Anomaly Detection Techniques Swish Analytics is an ...

Bay Football Club

Head of Data & Analytics

San Jose, CA · On-site

$140K/yr

While our community is our foundation, our love of football is our reason for being. We have the ... Ability to work non-traditional hours, including evenings, weekends, holidays, and travel with the ...

UT Federal Credit Union

Data Analyst

Knoxville, TN · On-site

Ability to collaborate effectively with both technical and non-technical stakeholders. Preferred ... Experience within financial services, banking, or credit unions. * Knowledge of advanced analytics ...

UT Federal Credit Union

Data Analyst

Knoxville, TN · On-site

Ability to collaborate effectively with both technical and non-technical stakeholders. Preferred ... Experience within financial services, banking, or credit unions. * Knowledge of advanced analytics ...

UT Federal Credit Union

Data Analyst

Knoxville, TN · On-site

Ability to collaborate effectively with both technical and non-technical stakeholders. Preferred ... Experience within financial services, banking, or credit unions. * Knowledge of advanced analytics ...

SumerSports LLC

Product Manager

... Football Data Analytics and AI experiences for our customers. It's a complex but exciting task to ... non-invasive way and iterate as needed. Job Overview: As we are a small company, this Product ...

SumerSports LLC

Sr. Product Manager

$129K - $170K/yr

... Football Data Analytics and AI experiences for our customers. It's a complex but exciting task to ... non-invasive way and iterate as needed. Job Overview: As we are a small company, this Senior ...

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Non Union Football Data Analytics information

What are the key skills and qualifications needed to thrive as a Non Union Football Data Analyst, and why are they important?

To thrive as a Non Union Football Data Analyst, you need strong quantitative analysis skills, a background in statistics or data science, and a deep understanding of football tactics and performance metrics. Proficiency with data analytics tools such as Python, R, SQL, and specialized sports analytics software is typically required. Excellent attention to detail, effective communication, and the ability to translate complex data into actionable insights are critical soft skills for this role. These skills and qualities are essential for identifying trends, informing coaching decisions, and providing a competitive edge through data-driven strategies.

What is non union football data analytics?

Non union football data analytics involves collecting, processing, and interpreting data related to football (soccer or American football) performance, statistics, and strategy, outside of unionized organizations. Professionals in this field use statistical methods, software tools, and data visualization techniques to help teams, coaches, and management make better decisions. This role typically focuses on providing insights about player performance, match outcomes, and tactical trends, often for private companies, media, or non-union clubs. The 'non union' aspect means that the role is not governed by a labor union, which can affect job conditions and benefits.

Do NFL teams hire data analysts?

Yes, NFL teams hire data analysts to evaluate player performance, develop strategies, and improve decision-making using statistical tools and data analysis techniques. These roles often require knowledge of sports analytics software, programming languages like Python or R, and a strong understanding of football metrics.

What are some typical challenges faced by professionals in Non Union Football Data Analytics roles?

Professionals in Non Union Football Data Analytics often encounter challenges such as consolidating and cleaning large, disparate datasets from different sources to ensure data accuracy. They must also communicate complex analytical findings to coaches and management in clear, actionable terms. Collaboration with scouts, coaching staff, and IT teams is frequent, requiring strong interpersonal skills and adaptability. Additionally, staying updated with the latest analytical tools and football trends is essential for delivering valuable insights that can influence team strategies.

How to get into data analysis in football?

To pursue a career in football data analysis, develop skills in statistics, data management, and programming languages like Python or R. Gain experience with sports analytics tools, understand football tactics, and consider obtaining certifications in data analysis or sports management to enhance your qualifications.

Can a data analyst become a sports analyst?

A data analyst can transition into a sports analyst role by gaining knowledge of sports-specific metrics, understanding game strategies, and developing expertise in sports data sources. Skills in data visualization, statistical analysis, and tools like SQL or Python are valuable in both roles. Certifications or experience in sports analytics can also facilitate this career shift.

How much do NFL data analysts make?

NFL data analysts typically earn between $60,000 and $100,000 annually, depending on experience, education, and the level of responsibility. Entry-level analysts may start lower, while experienced professionals with advanced skills in data visualization and statistical software can earn higher salaries in sports organizations or consulting firms.
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Non Union Football Data Analytics jobs near you

Sr. Football Data Scientist

SumerSports LLC

Remote

Full-time

Medical, Retirement

Re-posted 20 days ago

Job description

SumerSports is a leading football intelligence technology company that specializes in providing an innovative suite of products for 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 empowers teams with insights and tools to make informed decisions within salary cap constraints. The platform also serves the NCAA, offering insights around the transfer portal and more.
What sets us apart is our unique blend of big tech talent, data scientists, and former NFL personnel, who have a combined 600+ years of NFL experience. Our domain knowledge is augmented by AI and machine learning technologies to create a unique view into many aspects of Football.
We are seeking a motivated and skilled Senior Data Scientist to join our analytics team. You will be responsible for building, deploying, and refining a variety of football-focused analytical models, working with complex real-world datasets. You'll collaborate closely with other data scientists and engineers, ensuring our analytical products are accurate, robust, and impactful. The ideal candidate will demonstrate both strong technical skills and a proactive mindset, capable of independently taking projects from concept to deployment.
Responsibilities
  • Model Development and Analysis: Build and implement analytical football models, providing valuable insights to enhance our football analytics offerings. Conduct comprehensive data analysis to extract actionable insights.
  • Model Productionization: Ensure seamless deployment of machine learning and statistical models using Python, Databricks, and Spark. You will work on converting existing R models to Python as part of your initial responsibilities.
  • Large Dataset Management: Handle large datasets efficiently using Spark and Databricks, ensuring data integrity and performance optimization.
  • Collaboration: Work closely with other data scientists, analysts, and stakeholders to understand their needs and deliver high-quality analytical solutions.
  • Innovation: Identify and implement new tools, techniques, and best practices to enhance our data analytics capabilities.

Qualifications
Education: Advanced degree (Masters or PhD) in a quantitative discipline, or equivalent professional experience.
Experience: 4+ years of experience in data science, preferably in a sports analytics environment. (level commensurate with experience)
Technical Skills:
  • Proficiency in Python and experience with Databricks.
  • Strong programming skills in Python, including experience deploying models beyond exploratory notebooks.
  • Documented experience in football analytics, demonstrated through industry experience, public content, or
    significant independent projects. Examples would include working for an NFL or NCAA analytics department, working for a third party analytics provider, achievement in events such as the Big Data Bowl, or original football analytics Github repos.
  • Solid foundation in statistical modeling and machine learning methodologies.
  • Proven ability to independently identify and resolve data-related challenges in real-world datasets.
  • Effective communication skills, with experience explaining technical concepts clearly

Benefits
  • Competitive Salary and Bonus Plan
  • Comprehensive health insurance plan
  • Retirement savings plan (401k) with company match
  • Remote working environment
  • A flexible, unlimited time off policy
  • Generous paid holiday schedule - 13 in total including Monday after the Super Bowl

Apply