LA Galaxy, Associate Data Scientist - Soccer Operations - MLS

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The Associate Data Scientist supports the LA Galaxy's Soccer Operations department by contributing to analytical projects that inform player recruitment, tactical preparation, and performance evaluation. Working under the guidance of senior staff, this role assists in building datasets, developing baseline models, and producing reports that help coaches, scouts, and technical leadership make data-informed decisions. The Associate Data Scientist collaborates with analysts, coaches, and data engineering to ensure data pipelines, metrics, and tools are accurate, reliable, and aligned with the club's sporting objectives.

• Assist in preparing datasets and exploratory analyses that support player evaluation and recruitment decisions.
• Contribute to the development and testing of basic statistical or machine learning models used to compare players and identify potential targets.
• Build simple tools and visualizations that help the recruitment team interpret player performance across leagues and contexts.

• Support the creation of performance metrics and KPIs in collaboration with senior analysts and technical staff.
• Produce recurring reports and dashboards that track team and player trends over time.
• Help surface insights that inform coaching decisions and player development pathways.

• Assist in analyzing opponent tendencies, structures, and patterns using established workflows.
• Prepare summary reports and visualizations that contribute to match preparation and tactical planning.

• Work with data engineering to validate datasets, monitor model outputs, and ensure analytical tools remain accurate and up to date.
• Support documentation, testing, and quality checks for production workflows.

• Participate in meetings with Pro Analytics, Soccer Operations, and Performance teams to understand priorities and contribute to ongoing projects.
• Share analytical findings in a clear, concise manner and incorporate feedback from technical staff.

• BA/BS Degree (4-year) (Advanced Degree Preferred)- Mathematics, Computer Science, Statistics
• 1-2 years
  • Hands‑on modeling and data engineering experience working with sports data, preferably soccer‑specific datasets.
  • Experience building statistical models and applying machine learning techniques.
  • Experience managing production‑grade ML workflows
  • Experience with Azure Dev Ops/Git
  • Exposure to sports analytics or soccer‑specific data is preferred but not required.
• Proficiency in Python and SQL, with the ability to write clean, production‑quality code.
• Experience managing model development using tools such as MLflow or Azure AI, with the ability to maintain a production‑grade ML workspace.
• Strong statistical modeling foundation, including Bayesian methods, time series analysis, and spatial…