SVP - Data Engineering, Data Science & Analytics

AXS

San Francisco (CA)

On-site

USD 450,000 - 500,000

Full time

9 days ago

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Benefits offered by this job

Medical, dental, and vision insurance

Paid holidays

Vacation and sick time

Company-paid life insurance

Parental leave

401(k) plan

Flexible spending accounts

Wellness offerings

Job summary

AXS seeks a Senior Vice President of Data Engineering, Data Science & Analytics to unite global data platforms, models, and insights. You will lead a cross-functional team driving personalization, pricing, fraud prevention, forecasting, and decision-making across the business.

The role requires setting a unified vision, partnering with CTO and senior leaders, ensuring scalable, secure data practices, and delivering measurable business impact at scale.

Qualifications

15+ years in high-growth technology with leadership of data orgs spanning data engineering, data science, and analytics.
Experience building high-volume data platforms and production ML systems for consumer-facing/ transactional businesses.
Proven track record delivering data/AI roadmaps and scaling multidisciplinary teams.
Deep knowledge of modern data stacks and governance for compliant, secure data environments.

Responsibilities

Define and advance enterprise data, analytics, and AI strategy with executive leadership.
Own an integrated data roadmap across platforms, science, and analytics.
Oversee scalable data pipelines and evolving data lake/warehouse architectures.
Lead ML/AI model development for personalization, pricing, forecasting, and fraud detection.
Build analytics function with self-service BI and KPI frameworks.
Enforce data governance, privacy, and compliance standards.
Grow a global, high-performing data organization.
Collaborate with product, marketing, finance, and operations to embed data into products.
Drive operational excellence to reduce downtime and accelerate insights.
Communicate strategy and impact to CTO, board, and executives.
Manage budgets, headcount, and vendor spend effectively.

Skills

Executive leadership

Data & AI at scale

Strategic execution

Operational excellence

Global team leadership

Executive influence

Vendor & outsourcing management

Governance & compliance

Tools

Snowflake

Redshift

BigQuery

Airflow

dbt

Kafka

Kinesis

AWS

Job description

AXS is a global leader in live event ticketing and e-commerce, processing more than $4B in annual transactions. Each year, we connect millions of fans with the artists, teams, and experiences they love, powering ticket sales for concerts, festivals, sporting events, and theater at some of the world's most iconic venues.

At the forefront of transforming live entertainment through technology, AXS has continuously advanced the industry since our founding in 2011, making it easier than ever to discover events, secure the perfect seats, and enjoy unforgettable live experiences.

We are passionate about delivering transformative experiences for our customers. As we accelerate our vision to create a seamless journey around the entire lifecycle of a live event — from discovery and planning to participation and lasting memories — we are seeking a proven data leader to unify our data platforms, models, and insights into a single engine for growth. This is a unique opportunity to shape how live entertainment uses data, alongside some of the brightest minds in technology and the industry.

The Role

The Senior Vice President of Data Engineering, Data Science & Analytics will lead AXS' global data organization, owning the strategy, platforms, models, and insights that power personalization, pricing, fraud prevention, forecasting, and decision-making across the business. This spans our data lake and warehouse, streaming and batch pipelines, machine learning and AI models, business intelligence and reporting, and the governance practices that make trusted data available to Product, Marketing, Finance, Operations, and executive leadership.

This leader will define a unified vision and roadmap that connects data infrastructure, advanced analytics, and data science, ensuring the organization scales with transaction volume while remaining secure, compliant, and cost-effective — and that every investment translates into measurable business impact.

Success in this role requires close partnership with the CTO, SVP of Software Engineering, Product, and business leaders, as well as the ability to inspire, grow, and scale a world-class, multidisciplinary team. As a senior executive and visible leader, the SVP will champion a data-driven culture, foster innovation and scientific rigor, and ensure data and AI remain a competitive advantage for AXS.

Responsibilities

Partner with the CTO and executive leadership to define and advance AXS' enterprise data, analytics, and AI strategy.
Own an integrated roadmap across data platforms, data science, and analytics, balancing long-term vision with near-term priorities in personalization, pricing, fraud, and reporting.
Oversee the design, build, and operation of scalable batch and real-time data pipelines and the evolution of our data lake/warehouse architecture for performance, cost efficiency, and reliability.
Lead the data science function in developing and deploying machine learning and AI models for personalization, dynamic pricing, demand forecasting, fraud detection, and customer lifetime value, with mature MLOps practices.
Build and scale the analytics function, delivering self-service BI, executive dashboards, KPI frameworks, and experimentation (A/B testing) capabilities that drive decisions across the company.
Establish and enforce data governance, quality, lineage, privacy, and responsible AI standards, ensuring compliance with relevant data privacy and payment regulations.
Build and empower a high-performing global organization of data engineers, data scientists, and analysts, fostering a culture of innovation, collaboration, and continuous learning.
Collaborate with Product, Ticketing Strategy, Marketing, Finance, AEG, and other partners to identify high-value opportunities and embed data and models into products and operations.
Drive operational excellence through best practices, disciplined execution, and process improvements that increase reliability, reduce data downtime, and shorten time-to-insight.
Communicate strategy, progress, and business impact clearly to the CTO, executive team, and board-level stakeholders.
Manage operating budgets, headcount, and vendor spend effectively, ensuring financial accountability and sustainable growth.

Skills & Experience

Proven Executive Leadership: 15+ years in high-growth technology, including 8+ years leading data organizations spanning data engineering, data science, and/or analytics at scale.
Data & AI at Scale: Experience building high-volume data platforms and production ML systems supporting consumer-facing, e-commerce, or transactional businesses.
Strategic Execution: Demonstrated success defining and delivering data and AI roadmaps, managing multiple initiatives end-to-end, and scaling multidisciplinary organizations.
Technical Depth: Strong background with modern data stacks — data warehousing (Snowflake, Redshift, or BigQuery), orchestration (Airflow, dbt), streaming (Kafka, Kinesis), and cloud platforms (preferably AWS).
Data Science & ML: Deep understanding of statistical modeling, machine learning, experimentation design, and MLOps, with a track record of models that drive measurable revenue or cost outcomes.
Analytics & BI: Experience building analytics functions, KPI frameworks, and BI platforms (Tableau, Looker, Power BI, or similar) that enable data-driven decision-making at every level.
Reliability & Governance: Expertise in data quality, observability, lineage, and security practices, including compliance with data privacy and payment card standards.
Operational Excellence: Deep knowledge of Agile practices with a proven ability to optimize processes, define KPIs, and improve delivery at scale.
Global Team Leadership: Success leading distributed, diverse teams worldwide and building collaborative, high-performance cultures.
Executive Influence: Strong ability to partner with Product, Engineering, Finance, and Business Operations, translating complex data into clear business strategy for executive audiences.
Vendor & Outsourcing Management: Experience managing third-party vendors and outsourcing partnerships, ensuring quality, accountability, and alignment with strategic goals.