Football à Nouvelle-Zélande

SkillCorner collects sports data 100% automatically from a single camera feed. The company, now a global leader in its field of expertise, develops Computer Vision and Machine Learning algorithms that can detect all the moving objects (each player, the ball and the referee) in the image, locate them on the pitch, track them frame by frame, and recognize them. From this raw tracking data, SkillCorner produces Performance indicators, Game Intelligence metrics, and Visualizations that are used by clubs, national federations, and player agencies.

SkillCorner covers more than 150 competitions (both Women’s and Men’s), holds over 100 billion data points on more than 100 000 professional players. Trusted by more than 250 football, basketball and American Football teams worldwide, redefining their performance analysis, scouting, and recruitment workflows.

SkillCorner is looking for analysts to support its research & development work. In this role, you will work with SkillCorner and external data sources to develop frameworks and metrics to analyse players, teams and competitions with football data. The Research group focuses on surfacing trends and insights that are meaningful for data practitioners in football, while the Product group focuses on developing new metrics and supports product development.

• Create new metrics from innovative SkillCorner dynamic event data that capture player behaviors and support recruitment and player profiles
• Support product and AI teams in validation, testing and case-study development for new metrics
• Use historical data from multiple sources to identify key trends in football and develop analysis frameworks (Team profiles, Match Reviews…)
• Collaborate with internal teams to develop player and competition scores to help evaluate levels of competitions and predict player transferability

• Undergraduate or graduate degree in data science, computer science, engineering, or a related field.
• 2 years min experience in a Data analysis role
• Excellent football (soccer) knowledge
• Proficiency in Python, SQL, and Cloud Tools
• Past experience in working with sports data and long term projects
• Experience publishing academic/media research articles
• Experience working in ambiguous environments with minimal supervision; a self-starter who thrives on autonomy.
• Excellent analytical mindset, problem-solving skills, and ability to work collaboratively in teams.

• A unique combination of football expertise and data analysis skills
• Demonstrated modeling experience applied to sports
• Demonstrated ability to use statistical methods for metric development
• Demonstrated ability to produce long-form analytical work and communicate results
• Comfort working remotely while maintaining high productivity and effective communication.
• FORM and CV Screening
• Intro Chat
• At-home case study and presentation