Sr. Football Data Scientist

We are seeking a motivated and skilled Senior Data Scientist to join our analytics team. You will be responsible for building, deploying, and refining a variety of football-focused analytical models, working with complex real-world datasets. You'll collaborate closely with other data scientists and engineers, ensuring our analytical products are accurate, robust, and impactful. The ideal candidate will demonstrate both strong technical skills and a proactive mindset, capable of independently taking projects from concept to deployment.

Responsibilities

• Model Development and Analysis: Build and implement analytical football models, providing valuable insights to enhance our football analytics offerings. Conduct comprehensive data analysis to extract actionable insights.
• Model Productionization: Ensure seamless deployment of machine learning and statistical models using Python, Databricks, and Spark. You will work on converting existing R models to Python as part of your initial responsibilities.
• Large Dataset Management: Handle large datasets efficiently using Spark and Databricks, ensuring data integrity and performance optimization.
• Collaboration: Work closely with other data scientists, analysts, and stakeholders to understand their needs and deliver high-quality analytical solutions.
• Innovation: Identify and implement new tools, techniques, and best practices to enhance our data analytics capabilities.

Qualifications

Education: Advanced degree (Masters or PhD) in a quantitative discipline, or equivalent professional experience.

Experience: 4+ years of experience in data science, preferably in a sports analytics environment. (level commensurate with experience)

Technical Skills:

• Proficiency in Python and experience with Databricks.
• Strong programming skills in Python, including experience deploying models beyond exploratory notebooks.
• Documented experience in football analytics, demonstrated through industry experience, public content, or
  significant independent projects. Examples would include working for an NFL or NCAA analytics department, working for a third party analytics provider, achievement in events such as the Big Data Bowl, or original football analytics Github repos.
• Solid foundation in statistical modeling and machine learning methodologies.
• Proven ability to independently identify and resolve data-related challenges in real-world datasets.
• Effective communication skills, with experience explaining technical concepts clearly

Benefits

• Competitive Salary and Bonus Plan
• Comprehensive health insurance plan
• Retirement savings plan (401k) with company match
• Remote working environment
• A flexible, unlimited time off policy
• Generous paid holiday schedule - 13 in total including Monday after the Super Bowl