Looking for Football Data Analyst

Job Title: Football / Sports Data Analyst (Women in Football Analytics) Location: Remote ABOUT THE ROLE We are partnering with a specialized Football Analytics Lab dedicated to advancing women in sports analytics. We are looking for talented, passionate Female Data Analysts who are genuinely interested in working in football (soccer) to join upcoming data and performance analytics projects. In this role, you will turn raw match, event, and player tracking data into actionable tactical insights, scouting reports, and compelling visual stories for clubs, analysts, and football stakeholders. Whether you have existing experience in sports analytics or are a strong Data Analyst with a deep passion for football and a desire to work in the industry, we would love to review your profile and CV! WHAT YOU WILL DO - Match & Performance Analysis: Analyze football match event data and tracking data to evaluate team tactics, set-pieces, build-up play, and player performance. - Player Scouting & Recruitment Modeling: Build statistical models and custom metrics (e.g., xG, xA, progressive actions, PPDA, possession value) to identify, benchmark, and profile players across leagues. - Data Visualization & Storytelling: Create clear, engaging dashboards, pitch visualizations (pass maps, shot maps, heatmaps, radar charts), and automated reports for coaching staff and decision-makers. - Data Pipeline & Cleaning: Collect, clean, and structure multi-source football datasets (e.g., Opta, StatsBomb, Wyscout, FBref, SkillCorner, or public APIs). - AI & Predictive Insights: Apply statistical modeling and machine learning techniques to forecast match outcomes, injury risks, or player development trajectories. REQUIREMENTS & QUALIFICATIONS - Strong foundation in Data Analysis, Statistics, Data Science, Computer Science, or a related quantitative field. - Genuine passion for football (soccer) and a strong understanding of the game's rules, tactics, and modern football metrics. - Proficiency in Python (pandas, numpy, scikit-learn, matplotlib/seaborn, mplsoccer) or R for data manipulation and statistical modeling. - Solid experience with SQL and relational databases for querying large datasets. - Experience with BI and visualization tools such as Tableau, Power BI, Looker Studio, or custom web dashboards (Streamlit / Dash). - Excellent communication skills in English, with the ability to translate complex numbers into clear, football-friendly insights. - Female candidates are strongly encouraged to apply as part of our client's Women in Football Analytics initiative. NICE TO HAVE - Prior experience or personal portfolio projects working with football data providers (StatsBomb Open Data, Opta, Wyscout, Transfermarkt, Understat, FBref). - Familiarity with spatial/tracking data analysis or computer vision in sports. - A personal portfolio, GitHub repository, blog, or sample football visualizations/dashboards.