Data Scientist

Position Summary

Seeking a Data Scientist to provide analytics and data science support for a client within the Sports, Media, and Entertainment domain.

In this role, you will leverage analytics, machine learning, and AI to enable data-driven decision-making. You will work closely with stakeholders and have end-to-end ownership of building analytics solutions and data products.

This is an excellent opportunity for someone passionate about sports and interested in understanding both the emotional and commercial dynamics of the industry in a fast-paced, collaborative environment.

Key Responsibilities

• Collaborate with stakeholders in the sports sector to understand business objectives and deliver high-quality data science solutions
• Design and build end-to-end machine learning solutions and statistical frameworks focused on fan behavior
• Own the full model lifecycle including problem framing, feature engineering, model selection, cross-validation, and hyperparameter tuning
• Lead recurring analytical programs with an emphasis on reproducibility and automation
• Partner with data engineering teams to integrate model outputs into production systems and stakeholder-facing products
• Analyze data using tools such as SQL and Python, applying techniques like regression, decision trees, and machine learning models
• Extract actionable insights to support data-driven decision-making
• Support the integration of data science capabilities to solve business problems with measurable impact
• Contribute to continuous improvement of analytics processes and methodologies

Core Skills (Required)

• Bachelor’s degree in Economics, Mathematics, Computer Science/Engineering, Operations Research, or related field
• 2+ years of hands-on experience in a data science role with proven experience deploying models into production
• Strong proficiency in SQL for data extraction and analysis
• Strong programming skills in Python
• Solid foundation in statistics
• Experience with NLP techniques for processing unstructured data (e.g., survey data)
• Familiarity with Git and version control practices
• Understanding of MLOps concepts
• Strong problem-solving, analytical thinking, and communication skills
• Self-starter with the ability to manage time effectively and handle multiple priorities

Preferred Qualifications

• Master’s degree in Data Science, Analytics, Business Analytics, or related field
• Industry experience in Sports or Media/Entertainment
• Experience with additional data analysis and visualization tools
• Advanced statistical modeling skills
• Familiarity with data science governance practices

Interview Process

• Round 1: Assessment of problem-solving, structured thinking, data intuition, communication, and stakeholder awareness
• Round 2: Technical evaluation (Python, Machine Learning concepts, NLP fundamentals)
• Final Round: Client interview