Remote Soccer Data Scientist: Build Predictive Models

Swish Analytics; San Francisco (CA); Hybrid; USD 110,000 - 150,000; Full time

Job summary

Swish Analytics is seeking a Soccer Data Scientist to join our remote-USA team. You will own building production-grade models and feature sets for real-time sports analytics and betting products, leveraging domain knowledge and rigorous experimentation.

Qualifications include a Masters in data-related field, 2+ years of production experience in soccer or sports betting, strong ML and statistics knowledge, and proficiency in SQL, Python, AWS, GitHub, and CI/CD practices.

Qualifications

• Masters degree in Data Analytics, Data Science, Computer Science or related technical subject area.
• 2+ years of production-scale model development in Soccer or sports betting.
• Expertise in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and MCMC methods.
• 5+ years delivering machine learning/statistical models for sports or sports betting.
• Proficiency in relational SQL & Python.
• Experience with GitHub and CI/CD processes.
• Experience working in AWS environments.

Responsibilities

• Ideate, develop and improve ML and statistical models for Swish’s core algorithms.
• Develop contextualized feature sets using sports domain knowledge.
• Collaborate with data engineering and product teams to deploy models.

Skills

SQL

Python

Education

Masters degree in Data Analytics, Data Science, CS or related

Tools

GitHub

CI/CD

AWS

Job description

Swish Analytics is seeking a Soccer Data Scientist to join our remote-USA team. You will own building production-grade models and feature sets for real-time sports analytics and betting products, leveraging domain knowledge and rigorous experimentation.

Qualifications include a Masters in data-related field, 2+ years of production experience in soccer or sports betting, strong ML and statistics knowledge, and proficiency in SQL, Python, AWS, GitHub, and CI/CD practices.