Soccer Data Scientist
Swish AnalyticsFull Time
Junior (1 to 2 years)
Key technologies and capabilities for this role
Common questions about this position
You'll build Python automation scripts for listing, updating, and settling sports markets, develop data pipelines for sports data ingestion, implement DAGs for workflows, manage scheduled jobs, and own internal tooling for the Market Operations team.
Proficiency in Python for automation scripts, experience building data pipelines, DAG and workflow orchestration, scheduled job management with cron jobs, and developing internal tools are essential.
Deep knowledge of major leagues including NFL, NBA, MLB, NHL, MLS, NCAA, and international competitions is required to handle pre-game, in-play, and futures markets.
Kalshi hires really talented people, emphasizes working really hard, and enjoys the climb of building a new category in prediction markets.
Candidates with deep sports knowledge combined with strong engineering skills in Python, data pipelines, and automation, who are ambitious and exceptional, will stand out as the role evolves with the company's rapid scaling.
Regulated exchange for event contracts trading
Kalshi operates as a regulated exchange where traders can speculate on the outcomes of various events through a unique product called 'event contracts.' These contracts allow investors to bet on whether specific future events will happen, such as changes in Covid-19 statistics or legislative decisions in Congress. The platform expands the traditional futures market by addressing new economic risks, making it accessible to both individual investors and institutional traders who want to hedge or speculate on significant events. Kalshi earns revenue by charging transaction fees on trades made on its platform. What sets Kalshi apart from its competitors is its regulatory approval from the Commodity Futures Trading Commission (CFTC), which allows it to offer this new asset class in a compliant manner.