AXS-posted 7 days ago
$125,000 - $140,000/Yr
Full-time • Mid Level
Hybrid • Los Angeles, CA
501-1,000 employees

AXS connects fans with the artists and teams they love. Each year we sell millions of tickets to thousands of incredible events – from concerts and festivals to sports and theater – at some of the most iconic venues in the world. Since our founding in 2011, we’ve consistently pushed the industry forward and improved experiences for fans, making it easier than ever to discover events, find the perfect seats, and enjoy unforgettable live entertainment, and we continue to lead the evolution of our industry today. We’re passionate about improving the fan experience and providing game-changing solutions for our clients, and we’re always looking for smart, motivated people to help make it happen. Bring your enthusiasm, your big ideas, and your desire to team up with some of the best and brightest in technology and entertainment. The Role The Senior Data Scientist uses statistical modeling and machine learning tools to support business initiatives such as revenue maximization, personalization, and anomaly detection. The incumbent utilizes ticketing data at AXS to build and deploy scalable data science tools. This position collaborates with a dynamic team and works with various business stakeholders.

  • Machine Learning Modeling and Deployment - Contribute to the full data science lifecycle from model design, development, deploying/building data pipelines, and evaluating alignment with business goals
  • Business Strategy and Project Management - Translate requests and problems into frameworks for improving pricing strategy performance, driving value, and impacting business outcomes. Provide mentoring to junior data scientists and support the recruiting and hiring process for the data science team.
  • Business Collaboration - Effectively collaborate with business partners to communicate findings, understand key pricing problems, and define strategic priorities.
  • Technical Exploration and Research- Explore key development in data science and machine learning tools and algorithms. Identify needs, explore relevant data, and develop applicable tools to drive business decisions and strategy-making.
  • BS/MA/MS Degree (PhD preferred) in a Quantitative field such as Econometrics, Statistics, Operations Research, Machine Learning, Applied Mathematics, Computer Science, or related technical area
  • The experience level will vary based on the candidate’s degree level 1) PhD Candidates: 1-2 years related experience, or 2) Master of Science Candidates: 2-4 years related experience; or 3) Bachelor of Science Candidates: 5+ years of related experience
  • Experience with applied statistical, machine learning modeling, recommendation systems, and deployment experience
  • Experience on pricing strategy and revenue management
  • Experience with Git, bash/UNIX scripting
  • medical, dental and vision insurance
  • paid holidays, vacation and sick time
  • company paid basic life insurance
  • voluntary life insurance
  • parental leave
  • 401k Plan (with a current employer match of 3%)
  • flexible spending and health savings account options
  • wellness offerings
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