Zelus Analytics is hiring a
Machine Learning Engineer

Summary

Join Zelus Analytics as a Machine Learning Engineer to implement, automate, and optimize quantitative models for sports intelligence platforms in various sports. As a member of our team, you will support professional teams in their efforts to compete and win championships. We offer competitive salaries, equity, and benefits, including an annual incentive bonus plan and flexible PTO.

Requirements

• Academic and/or industry experience in back-end software design and development
• Academic, industry, and/or research experience with applied mathematical and predictive modeling (statistics, machine learning, optimization, and/or simulation)
• Experience with cloud infrastructure and distributed computing
• Fluency with Python (preferred), R, Scala, and/or other data-oriented and statistical programming languages
• Experience with relational databases and SQL development
• Familiarity working with Linux servers in a virtualized/distributed environment
• Strong software-engineering and problem-solving skills

Responsibilities

• Develop, validate, and automate quantitative models using statistics, machine learning, optimization, and simulation
• Develop, schedule, monitor, and maintain model training and prediction workflows
• Coordinate with broader engineering team to plan and implement changes to core infrastructure to support one or more sports
• Collaborate with data scientists to define and manage model productionalization and platform release plans
• Deploy REST APIs on top of fitted models using distributed computation to support real-time, client-facing integration
• Collaborate and communicate effectively in a distributed work environment
• Fulfill other related duties and responsibilities, including rotating platform support
• Research, design, and test cloud-based computational environments to support quantitative modeling at scale
• Collaborate with product and data science leads to define and manage implementation, validation, deployment, and release plans/logistics for our sports intelligence platforms
• Break down complex engineering projects into actionable work plans including proposed task assignments for one to four engineers and data scientists
• Provide guidance and technical mentorship for junior engineers
• Assist with recruiting and outreach for the engineering team, including building a diverse network of future candidates

Preferred Qualifications

• Expertise designing, developing, and optimizing the cloud infrastructure for large-scale, cloud-based analytics systems
• Experience with task orchestration and workflow automation tools (Airflow preferred)
• Experience adapting, retraining, and retooling in a rapidly changing technology environment
• Desire and ability to successfully mentor junior engineers

Benefits

• Competitive salaries
• Equity
• Annual incentive bonus plan
• Flexible PTO