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

Senior Product Designer

Manager

• Lead, coach, and develop a team of 8-10 people, including business, accounting, and technical consultants.
• Own overall delivery quality for the project portfolio.
• Ensure projects are delivered on time, within scope, and within budget.
• Serve as the top-level escalation point for project risks, issues, and blockers for both the client and managed employees; drive resolution and recovery plans.
• Build strong relationships with key client stakeholders and internal partners (Sales, Product, Support, etc.).
• Monitor project performance and execution metrics; identify patterns and improvement opportunities.

Services Manager

Consultant

• Collaborate with client management to design and implement Insight Analytics in their environment—defining the integrations, configurations, and targeted custom development that complement existing systems and deliver high business value.
• Design and implement custom data solutions using SQL (and other tools as needed) to support analytics use cases, KPIs, and executive reporting.
• Configure, extend, and support the Insight Analytics platform—data feeds, transformations, calculations, and visualizations—tailored to each client’s environment.
• Develop and optimize custom reports, stored procedures, and data processes that consolidate data across multiple casino systems to tell a clear, actionable story.
• Support the end‑to‑end implementation lifecycle: environment setup, integrations, data validation, UAT support, and go‑live activities.
• Troubleshoot and resolve technical issues in client environments, including data quality, performance, and integration problems.
• Produce clear technical documentation (data mappings, configuration guides, runbooks) that supports ongoing operations and client self‑sufficiency.
• Collaborate closely with Business Consultants, Product, and Engineering to ensure that solutions are aligned with client goals and Insight Analytics best practices.
• Provide production Support services for Insight Analytics clients, ensuring stability, reliability, and timely resolution of issues.
• Demonstrate outstanding customer service, professionalism, and relationship‑building skills in all client interactions.

Technical Consultant

Data Scientist

• Build and maintain statistical models, machine learning algorithms, and predictive analytics using gaming and behavioral data (segmentation, churn prediction and lifetime value models)
• Create anomaly detection systems for fraud and compliance monitoring
• Collaborate with data engineers to collect and preprocess data, and build and maintain data pipelines
• Design A/B testing frameworks and experiment analyses to test hypotheses and measure the effectiveness of solutions
• Document models and use data visualization tools to communicate insights and findings to stakeholders