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Staff Data Scientist

Viagogo

Viagogo

Data Science
New York, NY, USA
Posted on Mar 15, 2024
StubHub is on a mission to redefine the live event experience on a global scale. Whether someone is looking to attend their first event or their hundredth, we’re here to delight them all the way from the moment they start looking for a ticket until they step through the gate. The same goes for our sellers. From fans selling a single ticket to the promoters of a worldwide stadium tour, we want StubHub to be the safest, most convenient way to offer a ticket to the millions of fans who browse our platform around the world.
We're on the lookout for an accomplished Staff Data Scientist to join the Data Engineering & Analytics team at StubHub. In this role, you'll play a pivotal part in crafting and deploying cutting-edge machine learning models that drive business and operational choices within StubHub's dynamic ecosystem.
Our Data Science team serves as the backbone for enabling data-driven decisions across the organization, harnessing the potential of StubHub's consumer data through statistical and machine learning techniques. This involves creating both business-facing and customer-facing products, along with delivering user-friendly tools and clear explanations for non-technical users to enhance self-service capabilities.
As a Staff Data Scientist, you'll be the driving force in a business domain, steering the strategy and execution of model development. You will lead teams—first through influence and likely later through a small team of direct reports. We're seeking someone uniquely passionate about constructing models that empower data-driven decisions, equipped with robust engineering principles that enable full ownership throughout the model lifecycle. Additionally, effective communication skills to convey complex concepts to both technical and non-technical audiences are essential.
This role will be based out of our New York, NY, office and has a hybrid (3 in-person days per week) work schedule. Candidates with a strong preference for our Los Angeles, CA office location may also be considered.

What You'll Do:

  • Develop a foundational understanding of forecasting in the context of ticket pricing and business metrics
  • Build state-of-the-art machine learning models for which you own from design all the way through to production, and communicate your results to broad technical and non-technical audiences
  • Serve as a subject matter expert to the broader organization around on how to best build predictive modeling in the context of forecasting and pricing
  • Find and develop your own roadmaps with business partners and carry out project management and execution of your own work
  • Drive growth of junior team members and the data organization through venues such as workshops, best practices, and reading groups
  • Foster a culture of inclusion, results-oriented execution, open innovation, and limitless creativity across your team

What You've Done:

  • 8-10 years of relevant data science or machine learning experience and an MS. or Ph.D. degree in math, statistics, computer science, or other quantitative fields preferred.
  • Proficiency with transforming and analyzing large scale data with modern cloud computing platforms (e.g.,SparkSQL, BigQuery, Snowflake, Databricks), with high proficiency with query languages like SQL
  • Expert in Python or R and numerical and scientific libraries used for statistics and machine learning (e.g., Pandas, NumPy, SciPy, scikit-learn)
  • Experience in building production level models in cloud environments (e.g., AWS, Azure)
  • Demonstrated proficiency in time series modeling (GAMs, GLMs, ARs) and real-time forecasting are a nice-to-have
  • Passionate about working with non-technical stakeholders to understand, anticipate, and deliver on their data needs

What we offer:

  • Accelerated Growth Environment: Immerse yourself in an environment designed for swift skill and knowledge enhancement, where you have the autonomy to lead experiments and tests on a massive scale.
  • Top Tier Compensation Package: Enjoy a rewarding compensation package that includes enticing stock incentives, aligning with our commitment to recognizing and valuing your contributions.
  • Flexible Time Off: Embrace a healthy work-life balance with unlimited Flex Time Off, providing you the flexibility to manage your schedule and recharge as needed.
  • Comprehensive Benefits Package: Prioritize your well-being with a comprehensive benefits package, featuring 401k, and premium Health, Vision, and Dental Insurance options.
  • Team-Building Events: Engage in vibrant team events that foster camaraderie and collaboration, creating an atmosphere where your professional and personal growth are celebrated.
The anticipated gross annual base salary range for this role is $240,000 – $350,000 per year. Actual compensation will vary depending on factors such as a candidate’s qualifications, skills, experience, and competencies. Base annual salary is one component of StubHub’s total compensation and competitive benefits package, which also includes equity, 401(k), paid time off, paid parental leave, and comprehensive health benefits.
About Us
StubHub is the world’s leading marketplace to buy and sell tickets to any live event, anywhere. Through StubHub in North America and viagogo, our international platform, we service customers in 195 countries in 33 languages and 49 available currencies. With more than 300 million tickets available annually on our platform to events around the world -- from sports to music, comedy to dance, festivals to theater -- StubHub offers the safest, most convenient way to buy or sell tickets to the most memorable live experiences. Come join our team for a front-row seat to the action.
For California Residents: California Job Applicant Privacy Notice found here
We are an equal opportunity employer and value diversity on our team. We do not discriminate on the basis of race, color, religion, sex, national origin, gender, sexual orientation, age, disability, veteran status, or any other legally protected status.