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Selected role

Data Scientist (Freelancer)

FIFA Remote, US

Senior Full-time

**Description

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.**

**THE POSITION

These are your key tasks:**

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.

**YOUR PROFILE

We work hard at FIFA.

We are dedicated, ambitious and innovative.**

And we respect our values. Always.

For all roles, we seek talented people with an entrepreneurial spirit and a global mindset.

The specific competencies we require for this position are:

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.
Exerience 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.

**About FIFA

We are FIFA, the global governing body for football.**

Our vision is to make football truly global, diverse and inclusive, for the benefit of the entire world. The last FIFA World Cup in Qatar in 2022 attracted more than 5 billion viewers and the last FIFA Women's World Cup in Australia and New Zealand in 2023 was the greatest-ever FIFA Women's World Cup that inspired millions of girls and women around the globe. The opportunities for growth are exciting.

We are a modern organisation with over 800 passionate employees who are Living Football every day. Our headquarters are based in Zurich, Switzerland, and we have offices in Miami, Paris and Rabat, plus eleven regional offices from New Zealand to India, South Africa, Panama and Paraguay.

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