Machine Learning Engineer

Key Skills

Data science techniques, Effective communication skills, Machine learning techniques, Python Programming

Job Description

The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch. They can assist with optimizing the different aspects of the modeling process (Data Validation, Data Visualization, Data Stores & Structures, Feature Engineering, Model Training & Evaluation, Deployments) and improving a variety of Swish products. They will know when to “roll your own” and when to outsource a particular step in the modeling process. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues.

This position is 100% remote

Responsibilities:

• Design, prototype, implement, evaluate, optimize and monitor machine learning algorithms and related software systems to generate sports datasets and predictions with high accuracy and low latency
• Evaluate internal modeling frameworks and tools to optimize data scientist's modeling workflow
• Build, test, deploy and maintain production systems
• Maintain and promote best practices for software development, including deployment process, documentation, and coding standards
• Contribute to technical and product discussions, and share knowledge and ideas with colleagues across the company

Qualifications:

• Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area; PhD degree preferred
• Demonstrated experience developing data science modeling systems and infrastructure that scales
• Proficient in Probability Theory, Machine Learning, Inferential Statistics, Bayesian Statistics, Markov Chain Monte Carlo methods
• 5+ years of demonstrated experience developing and delivering effective machine learning models to serve business needs
• Experience with Python and modern machine learning frameworks
• Affinity for teamwork and collaboration with others to solve problems, share knowledge, and provide feedback
• Strong communication skills when discussing technical concepts with technical and non-technical colleagues

Base salary: $133,000-180,000