Data Scientist (Freelancer)

About

• Department: Legal & Compliance
• Employment Type: Freelance
• Location: Remote

We govern the beautiful game and ensure it's run with transparency and integrity.
Join our team in Miami and support us on our mission.

Responsibilities

• Support in the development and maintenance of an economic player‑valuation model.
• Conduct advanced data science projects (web scraping, NLP, machine learning, predictive modelling) to support multiple business units.
• Build and maintain interactive dashboards in Power BI for operational tasks and to analyse, monitor and refine internal processes.
• Support business users in implementing analyses for reports, publications and internal research projects.
• Design, implement and maintain ETL pipelines for various structured and semi‑structured data sources.
• Build and maintain data models used for Power BI reports.
• Actively collaborate with technical and non‑technical stakeholders, translating business requirements into robust analytical solutions.

Requirements

• Strong analytical thinking with the ability to break down complex modelling problems into structured, testable components.
• Solid quantitative reasoning and a rigorous, evidence‑based approach to problem‑solving.
• Intellectual curiosity and enthusiasm for exploring football, finance, and data‑driven questions.
• Ability to communicate complex technical findings clearly and visually, adapting the message to both technical and non‑technical audiences.
• High sense of ownership, reliability, and accountability for data quality, modelling choices, and delivered outputs.
• Collaborative team player who actively seeks feedback, contributes to shared standards, and supports knowledge exchange within the team.
• Comfort working in a fast‑moving environment with evolving requirements, and ability to prioritise effectively.
• Master’s degree in any technical/quantitative field (e.g. Data Science, Economics, Applied Mathematics, Statistics or related disciplines) or equivalent practical experience.
• 2-5 years of experience in data analytics, data modelling, machine learning, or quantitative research.
• Experience applying statistical, econometric, or financial‑economic models to real‑world datasets (e.g., valuation models, forecasting models, risk models).
• Proven experience translating business or research questions into robust analytical solutions, supported by clear data visualizations, effectively communicating insights to both technical and non‑technical stakeholders.
• Experience working with sports data — particularly football player performance, event data, or tracking data (Opta, Stats Perform, Hawkeye, SportsMonks, etc.) — is an advantage.
• Experience on the implementation of option‑value estimation techniques (Black‑Scholes) is an advantage.
• Fluent in English.
• Other languages can be a plus.
• Expertise in Python data science stack for statistical/econometric modelling.
• Experience working with SQL and relational databases.
• Experience working with business intelligence tools (Power BI is a plus).
• Experience with JavaScript, SSMS, SSDT, Node-RED and MS Azure cloud services is a plus.

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