Senior ML Engineer turned Product Manager — Disney · FIS · Accenture · SAP

Senior Machine Learning Engineer — Research · Disney

• Improved ad targeting and inventory yield by delivering core ML infrastructure for Disney’s Ad ML Platform — pipeline capabilities spanning 3 production models.
• Accelerated model deployment cycles and improved system reliability, partnering with data science and engineering to set platform benchmarks and architect an LLM-explainability layer.

Machine Learning Engineer · Fidelity Information Systems (FIS)

• Owned vision, strategy, and roadmap end to end for FIS’s Financial Intelligence Data Platform — built to handle 5M debit card transactions/day — running user research and discovery to eliminate developer bottlenecks.
• Launched a self-service ML platform on AWS (SageMaker), adopted by 25+ stakeholders across data science, ML engineering, and business analysis.
• Cut cloud inference costs and accelerated experimentation velocity for production XGBoost models.
• Brought production ML under governance: defined requirements for end-to-end MLOps automation — automated CI/CD and production-level compliance standards — with enterprise governance stakeholders.
• Led cross-functional delivery across infrastructure, security, compliance, and engineering as the team’s scrum master and all-hands demo presenter.

Technical Product Management Consultant · Accenture

• Mitigated $2M+ in regulatory non-compliance fines by owning end-to-end technical product management for an ML-driven ticketing classification system — aligning technical capabilities with governance requirements.
• Scaled automated triage to 300+ SQL security tickets daily by authoring the product requirements and system specifications for the classification engine.
• Eliminated operational bottlenecks across AWS cloud triage queues, building Python text-classification workflows directly with engineering.
• Led cross-functional alignment and people management across 8 direct reports, and pitched a data scripting product’s transition to an acquiring stakeholder team of 20.

• Reduced data pipeline errors by 70% by product-managing an end-to-end health dashboard with 8+ interactive visualizations for operations leaders.
• Improved hyper-scale hardware availability by 7%, defining data requirements and leading rollout of an automated predictive health reporting system across distributed data-center teams.

Associate Technical Consultant · SAP

• Delivered enterprise data migrations into SAP S/4HANA, aligning client requirements with technical implementation milestones across mobile, analytics, and data-transition teams.