Marketing

• Own strategy and execution for major conferences, trade shows, and regional events.
• Build clear, end-to-end plans: target account selection, internal invite strategy, pre-event outreach, onsite execution, and post-event follow-up.
• Coordinate pre-event outreach and sequencing across Sales and Marketing.
• Ensure strong onsite engagement with priority accounts and timely post-event follow-up with Sales.
• Turn trade shows and events into measurable pipeline (meetings, opportunities, revenue influence), not just brand presence.
• Help shape how CCT shows up in key communities through events, sponsorships, and targeted local engagement.
• Monitor industry happenings — stay current on trends, news, publications, and community activity within the gaming and hospitality space to identify timely engagement opportunities and keep field programs relevant.
• Define clear success metrics before every program and event — meetings booked, opportunities created, pipeline influenced, cost per meaningful engagement — so results are measured, not rationalized.

Field Marketing Lead

Machine Learning Engineer

• Build and maintain reproducible model training workflows on AWS (SageMaker, S3, Glue, etc.), making retraining, rollback, and experimentation routine rather than heroic.
• Deploy and operate real-time and batch inference services with full CI/CD pipelines, versioning, and safe rollout strategies (canary, shadow, A/B) so changes are deliberate and observable.
• Instrument production models for performance, data drift, latency, and errors — and automate retraining triggers when models drift out of tolerance.
• Maintain model lineage, auditability, and traceability to meet the compliance, governance, and reporting needs of the regulated gaming industry.
• Enforce least-privilege IAM, encryption, and secure data access patterns across the entire ML platform.
• Treat cost as a first-class engineering metric — right-size infrastructure, balance batch vs. real-time workloads, and continually reduce platform spend without sacrificing reliability.
• Collaborate with engineers, data scientists, and product teams to translate business problems into ML solutions, communicate tradeoffs clearly, and iterate based on feedback.
• Continuously explore new AWS services, ML frameworks, and deployment patterns to improve reliability, observability, and developer velocity on the ML platform.

Machine Learning Engineer, AWS

Product Designer

• Shape how casino leaders understand and act on their data by designing clear, unified views across gaming, hotel, food & beverage, and retail
• Lead design reviews and articulate the strategic rationale behind design decisions
• Design and prototype end-to-end workflows for high-stakes operations—reporting, cash management, and auditing
• Interview users and run user tests to deeply understand user needs and validate solutions
• Review user feedback, on-site observations, product analytics and stakeholder goals to identify opportunities to enhance user experience

Field Marketing Lead

Machine Learning Engineer, AWS

Senior Product Designer