Data Analyst

Our Company:

Statsbomb was founded in January 2017 to provide data, analytics, and consultancy to football clubs, media, and sports betting companies. Statsbomb continually undertake new research and is well-known in the analytics industry for providing unique insights into the game of football. We have developed our own proprietary industry-leading data collection and analytics software with a user-friendly high-vis front end.

In August 2024, we became Hudl Statsbomb as we were acquired by Hudl, the world's leading provider of cloud-based technology connecting video and data for the sports industry. The combination of Statsbomb's advanced data sets, innovative visualizations and powerful user interface and Hudl's integrated suite of video and data solutions will strengthen key workflows and provide deeper actionable insights to sports teams around the world.

Duties & Responsibilities:

• Analyze and interpret data to support business decision-making across departments.
• Build and maintain dashboards and reports using visualization tools (preferably Tableau).
• Write efficient and complex SQL queries to extract and manipulate data from various databases.
• Utilize Excel and Google Sheets for quick analysis, reporting, and collaboration with non-technical teams.
• Apply basic statistical methods to validate findings and provide accurate business recommendations.
• Support ad-hoc analysis and reporting needs with quick turnaround.
• Collaborate with cross-functional teams to identify data needs and opportunities for optimization.
• Present data-driven insights in a clear, concise, and impactful way to stakeholders at all levels.

Education & Qualifications:

• BSc. in Computer Science, Engineering or a related field.
• 2–4 years in a data analysis or business intelligence role.
• Experience working with cross-functional teams (e.g., product, marketing, operations).

Technical Skills:

• Strong proficiency in Excel and Google Sheets (pivot tables, lookups, advanced formulas).

• Expert in SQL: Ability to write complex queries, use CTEs, window functions, subqueries, and optimize query performance.

• Experience with data visualization tools (Power BI, Tableau – Tableau preferred) to build dashboards and visual stories.

• Basic Python: Familiarity with data analysis libraries like pandas, numpy, and basic scripting for automation or data wrangling.

• Understanding of basic statistics: descriptive stats, distributions, hypothesis testing, and correlation analysis.

• Experience with ETL processes and data cleaning techniques.

• Knowledge of data modeling and relational database design principles.

• Familiarity with version control tools like Git (e.g., managing Jupyter notebooks, SQL scripts, or dashboards in GitHub).

• Exposure to cloud-based data platforms (e.g., Google BigQuery, Amazon Redshift, Snowflake, or similar).

• Experience working with APIs and data extraction from various sources (CSV, JSON, databases, web scraping, etc.).

• Ability to document analysis processes, data definitions, and maintain data dictionaries.

Soft Skills:

• Excellent communication and presentation skills.

• Ability to work independently and collaborate effectively in a team environment.

• Strong analytical thinking and problem-solving mindset.
• Comfortable translating data into business stories and recommendations