Senior Machine Learning Engineer

Key Skills

Analytical and Problem solving, Data science techniques, Data Visualization, Effective communication skills, Machine learning techniques, Python Programming, SQL, UX design

Job Description

This person will drive pricing, curation, and merchandising projects from ideation to implementation. They will be a key person for the Merchandising defining objective and should be able to improve net revenue 5-10% over the next year. This is an amazing opportunity because merchandising is key to Gametime. Pricing tickets correctly and showing users the right inventory is essential to our business. The increased emphasis on sponsored means we are going to be really pushing the envelope on how we can drive our sellers to offer our users differentiated experiences, inventory, and prices. Lastly, we run lots of experiments- so this role is not a research project in the corner, but will have clear, measurable impact. Aside from the algorithms side, this person will collaborate heavily with product and design to inform the seat selection / UX roadmap.

What you'll be doing:

• Implement novel algorithms for pricing, curation (which tickets we show users), and merchandising
• Drive the future of the sponsored listing program
• Collaborate with product and design to inform the seat selection UX
• Run and analyze experiments with significant impact to net reven
• Our ideal candidate has:
• 5+ years industry experience in data science or machine learning
• Deep knowledge of statistics and experimentation
• Strong programming and data engineering skills (Python / SQL)
• Experience taking research prototypes to production

What we can offer you:

• Flexible PTO
• Equity
• Medical, dental, & vision insurance
• Life insurance and disability benefits
• 401K, HSA, pre-tax savings programs
• New equipment setup provided
• Diverse Family-forming benefits through Carrot Fertility
• Wellness programs
• Tenure recognition

$175,000 - $250,000 a year

At Gametime pay ranges are subject to change and assigned to a job based on specific market median of similar jobs according to 3rd party salary benchmark surveys. Individual pay within that range can vary for several reasons including skills/capabilities, experience, and available budget.