Real-Time Sports Analytics Scientist (Remote)

Swish Analytics; San Francisco (CA); On-site; USD 150,000 - 180,000; Full time

Job summary

Swish Analytics, a sports analytics startup, is hiring a data/ML engineer to develop transformer-like trader automation and low-latency systems. The role sits at the intersection of data science, trading, and data engineering to improve model accuracy and responsiveness to signals.

You will build, test, and deploy production-grade components, contribute to model development, and work with product teams across the tech stack. Remote from the USA or Canada.

Qualifications

• Bachelors in a technical field; Masters preferred.
• 4+ years delivering ML/statistical models for sports analytics or related domains.
• Strong foundation in probability, ML, statistics, and Bayesian methods.
• Proven ability to learn quickly in unfamiliar territory and communicate across teams.

Responsibilities

• Develop infrastructure for trader automation and system performance tracking.
• Build high-performance, low-latency components reacting to signals.
• Analyze live streaming data and translate to actionable decisions.
• Design tests to detect model changes due to interactions.
• Develop and deploy production-grade software with robust testing.
• Advance models and features driving Swish's core algorithms across sports.
• Collaborate with data engineering and product teams to deploy models.
• Continuously improve model performance via rigorous experimentation.

Skills

ML model development

Statistical analysis

Problem solving

Cross-team collaboration

Education

Bachelor's in Data Science / CS / Statistics

Master's degree preferred

Tools

Python

SQL

GitHub / CI/CD

AWS

Kafka

Docker

Kubernetes

Job description

Swish Analytics, a sports analytics startup, is hiring a data/ML engineer to develop transformer-like trader automation and low-latency systems. The role sits at the intersection of data science, trading, and data engineering to improve model accuracy and responsiveness to signals.

You will build, test, and deploy production-grade components, contribute to model development, and work with product teams across the tech stack. Remote from the USA or Canada.