Talantix.io
Smith Arnold Partners•02.03.26
AI SCORE 8.5

Sports Data Scientist - Remote Position

$90K–$120K/year
RemoteSports Analytics
Python•SQL•Data Visualization•Statistical Analysis•Predictive Modeling•Data Integrity

About the Role

We're hiring a Sports Data Scientist to join our innovative team at Smith Arnold Partners. This Sports Data Scientist remote position offers a unique opportunity to leverage your passion for sports analytics while working with NCAA basketball clients. You will play a crucial role in providing actionable insights that support decision-making within the collegiate sports landscape.

What You'll Do

  • Build predictive models utilizing insights from client and sport knowledge.
  • Conduct exploratory data analysis to identify data-driven insights on the transfer portal to collegiate programs.
  • Answer ad-hoc questions regarding transfer targeting.
  • Ensure data integrity and accuracy across several data sources.
  • Communicate complex data concepts effectively to non-technical audiences.

Requirements

  • Bachelor’s degree in Statistics, Computer Science, Data Science, or a related field.
  • Programming experience with proficiency in Python (pandas, polars, numpy) and SQL.
  • Experience generating data visualizations programmatically.
  • Deep understanding of sports, particularly football, baseball, or basketball.
  • Strong communication skills and ability to convey complex data concepts to non-technical audiences.
  • Strong self-motivation and curiosity to challenge traditional sports beliefs.
  • Attention to detail for accurate and timely report delivery.

Nice to Have

  • Experience playing or working with college football, baseball, or basketball teams.

What We Offer

  • Competitive salary ranging from $90,000 to $120,000 annually.
  • Fully remote work environment allowing for a flexible schedule.
  • Opportunities for professional development and growth within the company.
  • A collaborative and supportive company culture that values work-life balance.
  • Engaging projects that make a real impact in the sports industry.
Why This Job8.5 of 10

This Sports Data Scientist role offers a unique opportunity to work remotely while leveraging your passion for sports analytics in a collaborative environment.

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

Who Will Succeed Here

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Proficient in Python and SQL for data manipulation and analysis, with hands-on experience in libraries such as Pandas, NumPy, and SciPy to develop predictive models and perform statistical analysis.

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Self-motivated and disciplined, able to thrive in a fully remote work environment, demonstrating strong time management skills to balance multiple projects effectively while working independently.

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Experience in sports analytics with a deep understanding of NCAA basketball data, showcasing the ability to translate complex datasets into actionable insights for stakeholders in the collegiate sports industry.

Learning Resources

→Learn Python for Data Sciencecourse
→SQL for Data Sciencecourse
→Data Visualization with Pythonarticle

Career Path

Sports Data Scientist(Now)→Senior Sports Data Scientist(2-4 years)→Lead Data Scientist or Analytics Manager(4-6 years)

Market Overview

Market Size 2024
$20B
Annual Growth
12.5%
AI Adoption
45%
Investment
+50%
Labour Demand
+30%
Avg Salary
$95K

Skills & Requirements

Required
PythonSQLData Visualization
Growing in Demand
Machine LearningBig Data TechnologiesCloud Computing
Declining
R ProgrammingExcel-based Analytics

Domain Trends

Increased Use of Machine Learning in Sports Analytics
The sports analytics market is increasingly adopting machine learning techniques, with a projected growth rate of 15% annually as teams seek deeper insights from data.
Rise of Real-Time Data Processing
Real-time data processing technologies are being integrated into sports analytics, with 60% of organizations investing in real-time analytics solutions to enhance decision-making.
Growing Demand for Data Integrity Solutions
As data-driven decision-making becomes critical, 70% of sports organizations are prioritizing data integrity solutions, leading to a surge in demand for data scientists skilled in ensuring data quality.

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