Talantix.io
Swish Analytics•02.03.26
AI SCORE 8.5

Remote NFL Data Scientist - Sports Analytics

$120K–$150K/year
RemoteSports Analytics
Machine Learning•Statistical Analysis•Python•R•Data Modeling•Big Data•AWS•Google Cloud

About the Role

Swish Analytics is seeking a talented Remote NFL Data Scientist to join our innovative team. This role is pivotal in developing predictive sports analytics data products that cater to the dynamic world of sports betting. As a Remote NFL Data Scientist, you will leverage your expertise in machine learning and statistical modeling to create cutting-edge algorithms that enhance our sports betting offerings.

What You'll Do

  • Ideate, develop, and enhance machine learning and statistical models that drive Swish’s core algorithms for producing state-of-the-art sports betting products.
  • Utilize sports-specific domain knowledge to develop contextualized feature sets that improve model accuracy.
  • Contribute to all stages of model development, from creating proof-of-concepts and beta testing to collaborating with data engineering and product teams for deployment.
  • Continuously strive to improve model performance through rigorous offline and online experimentation.
  • Analyze results and outputs to assess model performance, identifying weaknesses to guide development efforts.
  • Adhere to software engineering best practices and contribute to shared code repositories.
  • Document modeling work and present findings to stakeholders and technical teams.

Requirements

  • 3+ years of experience in data science or a related field, with a focus on predictive modeling.
  • Strong proficiency in machine learning frameworks and statistical analysis.
  • Experience with programming languages such as Python or R.
  • Familiarity with sports analytics and betting markets is a plus.
  • Excellent problem-solving skills and ability to work in a fast-paced environment.
  • Strong communication skills to present complex data insights effectively.

Nice to Have

  • Experience with big data technologies (e.g., Hadoop, Spark).
  • Knowledge of cloud platforms (e.g., AWS, Google Cloud).
  • Background in sports science or a related field.

What We Offer

  • Competitive salary ranging from $120,000 to $150,000 per year.
  • Fully remote work environment with flexible hours.
  • Opportunity to work on innovative projects in the sports analytics space.
  • Collaborative team culture that values creativity and technical excellence.
  • Professional development opportunities and support for continuous learning.
  • Health and wellness benefits.
Why This Job8.5 of 10

This Remote NFL Data Scientist position at Swish Analytics offers a unique opportunity to work in the exciting field of sports analytics, with a competitive salary and the flexibility of remote work.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

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Proficiency in Python and R for data manipulation and statistical analysis, with a strong understanding of libraries such as Pandas, NumPy, and Scikit-learn to build predictive models for sports analytics.

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Self-motivated and adaptable work style suited for remote work, demonstrating the ability to manage time effectively and communicate asynchronously with team members across different time zones.

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Analytical mindset with a focus on continuous improvement and experimentation, leveraging big data technologies (like AWS or Google Cloud) to enhance modeling techniques and drive data-driven decision-making in sports betting.

Learning Resources

→Machine Learning with Pythoncourse
→Introduction to Statistical Learningbook
→Big Data on AWS: Getting Startedarticle

Career Path

Remote NFL Data Scientist - Sports Analytics(Now)→Lead Data Scientist - Sports Analytics(1-2 years)→Director of Data Science(3-5 years)

Market Overview

Market Size 2024
$15.7B
Annual Growth
40.2%
AI Adoption
63%
Investment
+150%
Labour Demand
+30%
Avg Salary
$120K

Skills & Requirements

Required
Machine LearningStatistical AnalysisPython
Growing in Demand
Deep LearningNatural Language ProcessingCloud Data Engineering
Declining
Traditional Statistical MethodsExcel-based Analytics

Domain Trends

Increased Use of Real-Time Data Analytics
By 2025, 70% of organizations will rely on real-time data analytics to enhance decision-making, particularly in sports analytics.
Integration of Machine Learning in Player Performance Analysis
Over 55% of NFL teams are expected to integrate machine learning models for player performance and health analytics by 2024.
Growth of Cloud-Based Sports Analytics Solutions
The market for cloud-based sports analytics is projected to grow by 35% annually, driven by the need for scalable data solutions in sports organizations.

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