The Role

We’re seeking a Senior Data Scientist to lead the science behind a best-in-class ticketing experience for fans, with a focus on the operational journey from ticket purchase through event entry. In this role, you will own and develop predictive and decisioning models that proactively identify and mitigate fulfillment issues, strengthen inventory validation, and optimize customer service policies — all while balancing fan experience with operational constraints.

You will work on problems where getting it right matters: predicting issues before they impact fans, identifying emerging pain points at scale, and turning moments of potential failure into opportunities to build trust and loyalty. This includes building and productionizing models on both structured and unstructured data, such as LLM-backed pipelines that extract actionable signals from customer communications and support interactions.

You will partner closely with product managers, analytics engineers, operations leaders, and other data scientists to translate ambiguous business problems into durable, production-ready data products, and to influence decisions that measurably improve the fan experience.

Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA 

What You'll Do

• Own the science behind ticket fulfillment: Drive reliability, ease of use, and customer satisfaction by crafting and deploying scalable, production-grade machine learning models that directly inform operational systems and decisions.
• Drive data-informed strategy: Work with operations partners to shape roadmaps, using analysis and modeling to identify, prioritize, and size high-impact opportunities that can be implemented and sustained at scale.
• Design for validation: Apply principles of experimentation and causal inference to ensure work products can be rigorously evaluated, defining offline validation and online testing strategies early in the design process.
• Build the data foundation: Partner with platform and analytics teams to ensure data availability and quality, including event instrumentation, batch and streaming ETL, feature stores, and monitoring for model performance, bias, and drift.
• Tell the story: Communicate trade-offs and impact to execs and non-technical partners; make the complex understandable and actionable.

What You've Done

• 5+ years of industry experience in data science or machine learning, with an MS or PhD in mathematics, statistics, computer science, or a related quantitative field preferred.
• Strong programming skills in Python, with experience using numerical and machine learning libraries such as Pandas, NumPy, SciPy, scikit-learn, and gradient-boosting frameworks (e.g., LightGBM, XGBoost).
• Demonstrated experience building, deploying, and iterating on production machine learning models in cloud environments (e.g., AWS, Azure), including post-deployment monitoring and improvement.
• Expertise working with large-scale data using modern analytics and compute platforms such as Snowflake, BigQuery, or Databricks, with strong proficiency in SQL.
• Proven ability to establish data science methodology in new or ambiguous domains, owning work end to end—from stakeholder alignment and problem framing to delivery and measurable impact.
• Excellent communication skills, with the ability to clearly articulate modeling assumptions, tradeoffs, and impact to both technical and non-technical audiences.

Nice to have:

• Experience applying machine learning to operational problem spaces such as ticket fulfillment, fraud detection, customer service, or trust and safety.
• Experience with production ML platforms and workflows, such as Metaflow or comparable systems (e.g., Airflow-based ML pipelines, Kubeflow, SageMaker Pipelines, Prefect, Flyte), including model versioning, scheduling, and monitoring.
• Experience selecting and applying appropriate causal inference approaches to evaluate model and policy impact, including methods such as uplift modeling, synthetic control, and BSTS.

What We Offer

• Accelerated Growth Environment: 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: Competitive base, equity, and upside that tracks with your impact.
• Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to 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.

The Role

We’re seeking a Senior Data Scientist to lead the science behind a best-in-class ticketing experience for fans, with a focus on the operational journey from ticket purchase through event entry. In this role, you will own and develop predictive and decisioning models that proactively identify and mitigate fulfillment issues, strengthen inventory validation, and optimize customer service policies — all while balancing fan experience with operational constraints.

You will work on problems where getting it right matters: predicting issues before they impact fans, identifying emerging pain points at scale, and turning moments of potential failure into opportunities to build trust and loyalty. This includes building and productionizing models on both structured and unstructured data, such as LLM-backed pipelines that extract actionable signals from customer communications and support interactions.

You will partner closely with product managers, analytics engineers, operations leaders, and other data scientists to translate ambiguous business problems into durable, production-ready data products, and to influence decisions that measurably improve the fan experience.

Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA 

What You'll Do

• Own the science behind ticket fulfillment: Drive reliability, ease of use, and customer satisfaction by crafting and deploying scalable, production-grade machine learning models that directly inform operational systems and decisions.
• Drive data-informed strategy: Work with operations partners to shape roadmaps, using analysis and modeling to identify, prioritize, and size high-impact opportunities that can be implemented and sustained at scale.
• Design for validation: Apply principles of experimentation and causal inference to ensure work products can be rigorously evaluated, defining offline validation and online testing strategies early in the design process.
• Build the data foundation: Partner with platform and analytics teams to ensure data availability and quality, including event instrumentation, batch and streaming ETL, feature stores, and monitoring for model performance, bias, and drift.
• Tell the story: Communicate trade-offs and impact to execs and non-technical partners; make the complex understandable and actionable.

What You've Done

• 5+ years of industry experience in data science or machine learning, with an MS or PhD in mathematics, statistics, computer science, or a related quantitative field preferred.
• Strong programming skills in Python, with experience using numerical and machine learning libraries such as Pandas, NumPy, SciPy, scikit-learn, and gradient-boosting frameworks (e.g., LightGBM, XGBoost).
• Demonstrated experience building, deploying, and iterating on production machine learning models in cloud environments (e.g., AWS, Azure), including post-deployment monitoring and improvement.
• Expertise working with large-scale data using modern analytics and compute platforms such as Snowflake, BigQuery, or Databricks, with strong proficiency in SQL.
• Proven ability to establish data science methodology in new or ambiguous domains, owning work end to end—from stakeholder alignment and problem framing to delivery and measurable impact.
• Excellent communication skills, with the ability to clearly articulate modeling assumptions, tradeoffs, and impact to both technical and non-technical audiences.

Nice to have:

• Experience applying machine learning to operational problem spaces such as ticket fulfillment, fraud detection, customer service, or trust and safety.
• Experience with production ML platforms and workflows, such as Metaflow or comparable systems (e.g., Airflow-based ML pipelines, Kubeflow, SageMaker Pipelines, Prefect, Flyte), including model versioning, scheduling, and monitoring.
• Experience selecting and applying appropriate causal inference approaches to evaluate model and policy impact, including methods such as uplift modeling, synthetic control, and BSTS.

What We Offer

• Accelerated Growth Environment: 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: Competitive base, equity, and upside that tracks with your impact.
• Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to 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.

The Data Science team, a part of the broader StubHub Data organization, is looking for an experienced, senior-level Data Science Manager to lead a growing team (currently 6, ranging from entry level DS to Staff+) that covers a wide range of data science disciplines.

StubHub is the largest secondary ticketing marketplace in the world, generating massive amounts of consumer data that are leveraged to tackle many unique and interesting predictive and inference problems across user acquisition, product recommendations, pricing optimization, ticket fulfillment mitigation, and business forecasting. As a Data Science Manager, you will need to work closely with business leaders and convert their long-term strategic goals into tangible machine learning projects executed by your team at a day-to-day level. Understanding when to provide oversight from a technical perspective, while being able to grow individuals, will be paramount in your team's long-term success.

You will also be responsible for the technical and personal growth of your team members, developing talent density through focused mentorship, strategic career development, and execution excellence. There will be a need for planning of team structure and growth as we put more investment into ML, especially understanding the best ways of building and applying generative AI solutions within our product.

You will be joining at a critical time for the Data Science practice and the company – while the value of this discipline has been established and there’s a high performing team in place, we are far from steady state. Key areas of investment from a vision and team planning perspective include establishing new pockets of deep technical expertise (e.g. causal inference, graph ML), advocating for best-in-class ML tooling/platform, and widening the reach of data science company-wide. As a senior leader of this team, you will be in charge of shaping and materializing that vision.

Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA 

What You'll Do

• Technical project scoping and planning
• Partner with cross-functional stakeholders across the business, executives, and data team
• Technical review and architecture oversight
• Recruitment and end-to-end talent growth development: Performance reviews, promotion recommendations, 360 feedback, etc
• Surface infrastructure needs and onboard solutions

What You've Done

• 8 - 10 years of relevant machine learning/data science in a fast-paced, high growth environment
• 8 - 10 years of experience managing high performant data science team.
• Strong programming and analytical ability with expertise in SQL and Python (TensorFlow, scipy, scikit-learn, PyTorch, statsmodels)
• Experience with modern workflow orchestration used in machine learning, e.g.,Metaflow, ZenFlow, Airflow
  
  
• Nice to Haves
  • Worked at a consumer tech company
  • Experience with GenAI/LLM/Agentic workflows in a production setting
  • Hands-on experience with graph based machine learning and recommendation systems

What We Offer

• Accelerated Growth Environment: 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: Competitive base, equity, and upside that tracks with your impact.
• Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to 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.

The Data Science team, a part of the broader StubHub Data organization, is looking for an experienced, senior-level Data Science Manager to lead a growing team (currently 6, ranging from entry level DS to Staff+) that covers a wide range of data science disciplines.

StubHub is the largest secondary ticketing marketplace in the world, generating massive amounts of consumer data that are leveraged to tackle many unique and interesting predictive and inference problems across user acquisition, product recommendations, pricing optimization, ticket fulfillment mitigation, and business forecasting. As a Data Science Manager, you will need to work closely with business leaders and convert their long-term strategic goals into tangible machine learning projects executed by your team at a day-to-day level. Understanding when to provide oversight from a technical perspective, while being able to grow individuals, will be paramount in your team's long-term success.

You will also be responsible for the technical and personal growth of your team members, developing talent density through focused mentorship, strategic career development, and execution excellence. There will be a need to plan team structure and growth as we invest more in ML, especially to understand the best ways to build and apply generative AI solutions within our product.

You will be joining at a critical time for the Data Science practice and the company – while the value of this discipline has been established and there’s a high-performing team in place, we are far from steady state. Key areas of investment from a vision and team planning perspective include establishing new pockets of deep technical expertise (e.g., causal inference, graph ML), advocating for best-in-class ML tooling/platform, and widening the reach of data science company-wide. As a senior leader on this team, you will be responsible for shaping and realizing that vision.

Location: Hybrid (3 days in office/2 days remote) – New York, NY or Century City, CA 

What You'll Do

• Technical project scoping and planning
• Partner with cross-functional stakeholders across the business, executives, and data team
• Technical review and architecture oversight
• Recruitment and end-to-end talent growth development: Performance reviews, promotion recommendations, 360 feedback, etc
• Surface infrastructure needs and onboard solutions

What You've Done

• 8 - 10 years of relevant machine learning/data science in a fast-paced, high growth environment
• 8 - 10 years of experience managing high performant data science team.
• Strong programming and analytical ability with expertise in SQL and Python (TensorFlow, scipy, scikit-learn, PyTorch, statsmodels)
• Experience with modern workflow orchestration used in machine learning, e.g.,Metaflow, ZenFlow, Airflow
  
  
• Nice to Haves:
  • Worked at a consumer tech company
  • Experience with GenAI/LLM/Agentic workflows in a production setting
  • Hands-on experience with graph-based machine learning and recommendation systems

What We Offer

• Accelerated Growth Environment: 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: Competitive base, equity, and upside that tracks with your impact.
• Flexible Time Off: Enjoy unlimited Flex Time Off, giving you the flexibility to manage your schedule and take time to 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.