Data Analyst (Direct-to-Consumer Streaming)

Tennis Channel•Santa Monica, CA

29d•$130,000 - $150,000•Onsite

About The Position

Tennis Channel is expanding its Direct-to-Consumer (DTC) Streaming team and is seeking a highly motivated and detail-oriented Data Analyst to help shape the future of our digital products! In this role, you’ll collaborate with the Director, Product Design to develop analytics initiatives that drive strategic decision-making and optimize user experience. You’ll define and maintain key performance metrics, build scalable dashboards and data pipelines, and transform complex datasets into actionable insights that guide product innovation and business growth—all while bringing a strong curiosity for data analytics and business intelligence, a critical-thinking mindset, exceptional attention to detail, and a commitment to data accuracy. Our ideal candidate is a proactive self-starter who thrives in fast-paced, collaborative environments, asks the right questions to uncover hidden insights, and is eager to grow their technical skill set in areas like machine learning and data engineering. This is an exciting opportunity for a data-driven problem solver who’s passionate about streaming, sports, and technology and eager to influence how fans engage with the game across platforms! This role is onsite and based in Santa Monica, CA.

Requirements

Bachelor’s degree in computer science, mathematics, economics, data science, statistics, or a related field
Proficiency in SQL, including aggregation, joins, window functions, and data transformations
Strong analytical and problem-solving skills, with the ability to interpret and communicate complex data
Intermediate proficiency in Microsoft Excel, PowerPoint, and Word
Experience cleaning and processing large datasets, handling missing values, and resolving data quality issue
Familiarity with data visualization tools such as Looker, Sigma, or Omni (or similar BI tools)
Experience working with relational databases (e.g., PostgreSQL, Redshift, Snowflake)

Nice To Haves

Basic Python skills for data analysis are a plus
familiarity with non-relational databases such as Elasticsearch is a plus

Responsibilities

Partner with the Data Science and Business Intelligence teams to define, measure, and monitor key metrics across customer engagement, retention, and product performance.
Conduct quantitative and statistical analyses to uncover trends, identify performance drivers, and inform strategic recommendations.
Design, execute, and evaluate A/B tests to support experimentation and feature optimization.
Develop and maintain dashboards and reports for cross-functional teams including Finance, Marketing, and Product.
Clean, process, and validate data from multiple sources, ensuring completeness and reliability.
Translate analytical findings into clear, actionable insights for both technical and non-technical stakeholders.
Document business requirements, analytical processes, and data definitions to ensure reproducibility and transparency.