Role Purpose

• Help design the foundations of Scorpii Score’s prediction logic.
• Build statistical models and turn raw football-related data into structured, meaningful insights that power core features.

Key Responsibilities

• Build and refine statistical models for match prediction and scoring logic.
• Explore datasets to identify patterns, trends, and modeling opportunities.
• Use Python to create model prototypes, baselines, and evaluation scripts.
• Use SQL to extract, prepare, and validate data from internal databases.
• Collaborate with the AI/ML team to compare statistical approaches with ML-based alternatives.
• Produce clear documentation on modeling assumptions, methods, and results.

Profile — You’re good if you…

• Have strong skills in Python and SQL.
• Understand statistical modeling basics (regression, probability distributions, sampling, evaluation).
• Enjoy working with numbers, trends, and structured logic, and want to apply statistics to football analytics.
• Are curious, analytical, and comfortable exploring ambiguous datasets.

What You’ll Gain

• Experience shaping the statistical engine behind Scorpii Score and designing product baselines.
• Opportunities to experiment with football performance datasets and build practical prototypes.
• A hands-on role interacting with AI/ML engineers and product owners in a collaborative environment.