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About the Role

Join Swish Analytics to develop infrastructure for a system that optimizes simulation outputs using various signals. This role bridges data science, trading, and data engineering to enhance trader automation algorithms, improve reaction times to signals, and boost model accuracy.

Responsibilities

• Develop infrastructure for trader automation and system performance tracking.
• Develop high-performance, low-latency products to react to external and internal signals.
• Analyze live-streaming data and translate it into actionable decisions.
• Design and set up tests to detect unexpected model changes from manual interactions.
• Build, test, debug, and deploy production-grade components using extensive experience.
• Ideate, develop, and improve machine learning and statistical models that drive Swish's core algorithms.
• Develop contextualized feature sets drawing on sports-specific domain knowledge.
• Contribute across all stages of model development, from proof-of-concept to deployment.
• Constantly improve model performance through rigorous experimentation.
• Assess model performance, identify weaknesses, and direct development efforts.
• Document work and present it clearly to technical and non-technical partners.

Requirements

• Bachelor's degree in Data Science, Statistics, Computer Science, Applied Math, or a related technical field; Master's strongly preferred.
• 4+ years of experience developing and delivering effective machine learning and/or statistical models for sports analytics or sports betting.
• Experience in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, and Markov Chain Monte Carlo methods.
• Excellent analytical and problem-solving abilities with a drive to learn quickly.
• Experience with Python and relational SQL.
• Strong foundation with source control (GitHub) and CI/CD processes.
• Strong foundation working in AWS environments.
• Ability to partner across teams on complex problems and communicate clearly with diverse audiences.

Skills

• Python
• SQL
• GitHub
• AWS
• Probability Theory
• Machine Learning
• Inferential Statistics
• Bayesian Statistics
• Markov Chain Monte Carlo methods
• Kafka
• Docker
• Kubernetes

Location

• USA
• Canada

Work Type

• Remote
• Full-time

Experience Level

• 4+ years

Education Level

• Bachelor's degree
• Master's degree

Salary/Compensations

• $150,000

About the Company

• Swish Analytics is a sports analytics, betting, and fantasy startup building the next generation of predictive sports analytics data products.
• We believe oddsmaking is a challenge rooted in engineering, mathematics, and sports betting expertise, not intuition.
• We seek team-oriented individuals with a passion for accurate, predictive real-time data who can execute in a fast-paced, creative, and evolving environment while maintaining technical excellence.
• Our challenges are unique, and we encourage comfort in uncharted territory and passion for building systems to support diverse products and clients.

Equal Opportunity

• Swish Analytics is an Equal Opportunity Employer. All candidates who meet the qualifications will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, pregnancy status, genetic, military, veteran status, marital status, or any other characteristic protected by law.
• The position responsibilities are not limited to those outlined above and are subject to change.
• At the employer's discretion, this position may require successful completion of background and reference checks.