Data Scientist II - Fan Experience & Operations

Job Description Summary

Job Title: Data Scientist

Company

StubHub

Location

• New York, NY (Hybrid: 3 days in-office, 2 days remote)
• Century City, CA (Hybrid: 3 days in-office, 2 days remote)

StubHub is seeking a Data Scientist to lead the development of predictive and decisioning models focused on the operational ticketing journey (purchase through entry). The role involves mitigating fulfillment issues, strengthening inventory validation, and optimizing customer service policies by balancing fan experience with operational constraints. The successful candidate will build production-ready models on structured and unstructured data (including LLM-backed pipelines) and partner with cross-functional teams to solve ambiguous business problems.

Key Responsibilities

• Own the science behind ticket fulfillment: Craft and deploy scalable, production-grade machine learning models to inform operational systems.
• Drive data-informed strategy: Collaborate with operations to shape roadmaps and prioritize high-impact opportunities.
• Design for validation: Apply experimentation and causal inference principles to rigorously evaluate work products and define testing strategies.
• Build the data foundation: Partner with platform teams to ensure data quality, event instrumentation, ETL pipelines, and model monitoring.
• Communication: Translate complex technical concepts and trade-offs to executives and non-technical partners.

• Experience: 2-4 years of industry experience in data science or machine learning.
• Education: MS or PhD in Mathematics, Statistics, Computer Science, or a related quantitative field.
• Programming: Strong proficiency in Python with experience in numerical/ML libraries (Pandas, NumPy, SciPy, scikit-learn, LightGBM, XGBoost).
• Modeling: Demonstrated experience building, iterating, and rigorously validating machine learning models.
• Data Platforms: Expertise with large-scale data tools (Snowflake, BigQuery, Databricks) and strong SQL proficiency.
• Soft Skills: Excellent communication skills to articulate assumptions and impact to diverse audiences.

• Experience applying ML to operational problem spaces (ticket fulfillment, fraud detection, trust and safety).
• Experience with production ML platforms (Metaflow, Airflow, Kubeflow, SageMaker, Prefect, Flyte).
• Experience with causal inference methods (uplift modeling, synthetic control, BSTS).

Base Salary Range: $180,000 — $250,000 USD

Note: Actual compensation varies based on qualifications and experience. Total compensation includes equity, 401(k), PTO, and benefits.

Benefits

• Acelerated Growth Environment (autonomy to lead experiments)
• Flexible Time Off (Unlimited)
• Comprehensive Benefits (Health, Vision, Dental)
• 401(k) Plan
• Paid Parental Leave
• Competitive Equity and Bonus structure