Remote Sports Analytics Specialist

Placements24; Kempton Park; Remote; ZAR 1,481,000 - 2,468,000; Full time

Benefits offered by this job

Health insurance

Remote-friendly culture

Conference & training budget

Home office stipend

Paid time off

Job summary

Placements24 is seeking a highly analytical Sports Analytics Specialist to join a remote-first team. You will dissect large data sets related to sports performance, fan engagement, and market trends to deliver actionable insights and strategic recommendations to stakeholders worldwide.

The role requires a Master’s/PhD in a quantitative field, 5+ years in data analysis with sports analytics, and strong Python/R, SQL, and visualization skills.

Qualifications

• Master's or PhD in a quantitative field.
• 5+ years in data analysis and statistical modeling with a focus on sports analytics.
• Proficiency in Python or R and Pandas/NumPy.
• Strong SQL and data visualization skills; ML knowledge.
• Excellent communication and remote collaboration skills.

Responsibilities

• Collect, clean, and analyze large datasets related to sports performance, fan engagement, market trends, and operational efficiency.
• Develop and implement statistical models, ML algorithms, and predictive analytics for player performance, game strategies, and audience behavior.
• Create reports and visualizations to communicate findings and recommendations to non-technical stakeholders.
• Collaborate with performance coaches, scouting teams, and marketing to identify data-driven opportunities.
• Design and evaluate experiments to test hypotheses and measure impact of interventions.
• Stay updated on trends and technologies in sports analytics, data science, and AI.
• Contribute to data infrastructure and tools to enhance accessibility and analysis capabilities.
• Work independently and in a globally distributed team with timely delivery of outputs.
• Present findings and strategic recommendations to senior management.

Skills

Python

R

SQL

Pandas

NumPy

Tableau

Power BI

Matplotlib

Machine learning

Communication

Remote collaboration

Education

Master's degree or PhD in Statistics/Data Science/Mathematics/Economics

Tools

Tableau

Power BI

Matplotlib

Pandas

NumPy

Job description

About the Role

Our client is at the forefront of innovation in the Leisure & Sports sector and is looking for a highly analytical and data-driven Sports Analytics Specialist to join their fully remote team. This role is designed for a professional who thrives on dissecting complex data sets to uncover actionable insights that drive strategic decision-making. Based anywhere in the world, you will work closely with various departments, including performance analysis, marketing, and business development, to leverage data for competitive advantage. The ideal candidate will have a strong quantitative background, exceptional problem-solving skills, and a passion for applying advanced analytics to the world of sports. This is a unique opportunity to contribute to a forward-thinking company and shape the future of sports analytics from a remote setting. You will be empowered to explore new data sources, develop sophisticated models, and translate complex findings into clear, understandable recommendations for stakeholders. Our client is committed to a remote-first culture, ensuring seamless collaboration and productivity for all team members, regardless of their physical location. Embrace the freedom and flexibility of a role that values results and impact over presence.

Key Responsibilities

• Collect, clean, and analyze large datasets related to sports performance, fan engagement, market trends, and operational efficiency.
• Develop and implement statistical models, machine learning algorithms, and predictive analytics to provide insights into player performance, game strategies, and audience behavior.
• Create comprehensive reports and visualizations to communicate findings and recommendations to non-technical stakeholders across the organization.
• Collaborate with performance coaches, scouting teams, and marketing departments to identify data-driven opportunities for improvement and innovation.
• Design and evaluate experiments to test hypotheses and measure the impact of various interventions or strategies.
• Stay abreast of the latest trends and technologies in sports analytics, data science, and artificial intelligence.
• Contribute to the development of data infrastructure and tools to enhance data accessibility and analysis capabilities.
• Work independently and as part of a globally distributed team, ensuring timely delivery of high-quality analytical outputs.
• Present findings and strategic recommendations to senior management and other key decision-makers.

Requirements

• A Master's degree or PhD in Statistics, Data Science, Computer Science, Mathematics, Economics, or a related quantitative field.
• Proven experience (5+ years) in data analysis and statistical modeling, with a significant portion focused on sports analytics or a closely related domain.
• Proficiency in programming languages such as Python or R, and experience with data manipulation libraries (e.g., Pandas, NumPy).
• Expertise in SQL for data extraction and manipulation.
• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib).
• Strong understanding of machine learning techniques and their application.
• Excellent communication and presentation skills, with the ability to explain complex technical concepts to a diverse audience.
• Demonstrated ability to work autonomously in a remote environment and manage multiple projects simultaneously.
• A genuine passion for sports and a strong desire to apply analytical skills to the industry.
• Familiarity with various sports data sources and performance metrics.

Benefits

• Highly competitive remote salary with a generous bonus structure.
• Comprehensive health, dental, and vision insurance coverage.
• Flexible working hours and a true remote work environment.
• Opportunities for continuous learning and professional development in a cutting-edge field.
• Generous home office setup stipend.
• Annual budget for conferences and training.
• Paid time off and holidays.
• Access to internal and external data science communities.
• A collaborative and inclusive global team culture.