FVP of Data Products & Monetization

Axos Bank

Target Range:

$165,000.00 /Yr. - $190,000.00 /Yr.

Actual starting pay will vary based on factors including, but not limited to, geographic location, experience, skills, specialty, and education.

Eligible for an Annual Discretionary Cash Bonus Target: 10%

Eligible for an Annual Discretionary Restricted Stock Units Bonus Target: 10%

These discretionary target bonuses may be awarded semi-annually based upon your achievement of performance goals and targets.

About This Job

This role will report onsite at our HQ in San Diego, California. Remote or Hybrid is not available.

Axos is seeking FVP, Data Products & Monetization to lead it’s Data Science and Data Monetization charter. This hands-on position is responsible for leveraging data to drive revenue generation, enhance customer engagement, and optimize business operations. This position combines strategic vision, technical expertise, and business acumen to monetize data assets, build advanced analytics capabilities, and deliver innovative data solutions that drive growth, efficiency, and customer value. The ideal candidate will have a strong background in Data Science, Machine Learning, Data Engineering, and Revenue Generation Strategies.

Responsibilities:
Data Monetization Strategy & Execution - Develop and execute a comprehensive strategy to monetize internal and external data assets. Identify new revenue streams through data-as-a-service offerings, partnerships, and licensing models. Align monetization initiatives with business objectives and market opportunities.

Advanced Analytics Leadership - Lead the design and deployment of advanced analytics, machine learning, and AI solutions. Drive innovation in predictive, prescriptive, and agentic AI capabilities for business optimization. Champion data-driven decision-making across all business units, product leadership and stakeholders.

Cross-Functional Collaboration - Work closely with engineering, data science, product, marketing, and business stakeholders. Translate complex technical concepts into business value for non-technical audiences. Collaborate with GTM and Customer Success teams for successful product launches and adoption. Ideate and work with lines of business to build proof of concepts.

Product Management for Data Products - ROI modeling and business case development. Translating technical concepts into business value. Rapid prototyping and proof-of-concept development. Roadmap planning, feature prioritization, and release management. Maintain Data Product Lifecycle - Ownership, discoverability, interoperability, and lifecycle management, and drive product evolution through continuous iteration based on KPIs (accuracy, latency, ROI).

Thought Leadership & Innovation - Monitor & adopt industry trends and emerging technologies to maintain competitive advantage. Provide executive-level guidance on Data Strategy, Data Monetization, Agentic AI, AI/ML and Advanced Analytics. Foster a culture of innovation and continuous improvement within the organization.

Key Success Measures

• Revenue Growth: Through data-driven products and services
• Customer Experience Enhancement: Via personalized CX and AI/ML powered solutions
• Operational Efficiency: Leveraging advanced analytics for optimization
• Model performance: accuracy, latency, error rates

Requirements:

• Bachelor’s degree in Engineering, Data Science, Computer Science, Statistics, or a related field; advanced degree preferred.
• 12+ years in Data Engineering.
• 5+ years of hands-on experience in Data Science, Machine Learning, Advanced Data Management, and Data Monetization.
• Proven track record of hands-on leadership and delivering successful data-driven projects, including proven track record in driving revenue growth by leveraging data.
• Programming & Data Manipulation - Python (Data Science, ML frameworks like scikit-learn, TensorFlow, PyTorch), SQL (complex queries, optimization)
• Machine Learning & AI - Predictive and prescriptive modeling, Model deployment and monitoring (ML Ops) and Agentic AI concepts (autonomous agents, multi-agent orchestration, MCP, Cursor, LangChain, LangGraph, Spark)
• Data Engineering - Building and maintaining data pipelines (ETL/ELT, Fivetran, dbt, Lakebase, Spark SQL), Experience with data warehouses, Databricks Lakehouse (Mosaic, Agentbricks, Notebooks, Lakeflow, Tabular), and expertise in Data Streaming
• Data Visualization & BI - Tools like Power BI, Tableau, and Building interactive dashboards and API-driven visualizations
• Strong understanding and appreciation of Data G