Maeliza Seymour

- Improved customer adoption by +17% through customer segmentation. Developed the use case (needs and prioritization), implemented data analysis and segmentation solution (PoC), and reported insights into actionable information for the marketing team.

- Reduced production incident detection time by 85%.

Prioritized PoC scope, implemented data pipeline (cleaning and analysis), and configured an internal dashboard for easy user access.

- Reconciled data from various sources: Salesforce, internal databases, IoT. Used PowerBI to create an adequate data model and monitor data consistency and quality.

- Improved data quality by mapping existing data and covered processes. Monitored data completeness and the collection of missing data. Implemented an action plan with the technical team to increasingly expand the scope of data collected (from 1.5 to 3.4 GB per day).

- Implemented the first enterprise data PoC in one month. Coordinated stakeholders (business, technology, marketing, and support) using the Agile methodology.

- Designed, prioritized, and planned use cases for a data-centric approach. Identified business needs and priorities, mapped existing and missing data, and defined implementation and monitoring priorities

- Launched an AI-powered product MVP in 1.5 months.

Set up the technical roadmap for AI algorithms. Iterated product development with increasingly large datasets and more complex algorithms using the Lean AI methodology. We achieved a +10% improvement over existing benchmarks in 6 months.

- Achieved Product-Market fit in 6 months.

Transformed product vision into a tactical plan, conducted user interviews to strategically prioritize the product roadmap.

- Grew the user base from 100 to 30,000 in six months.

- Recruited and managed a technical team of 5 people with a monthly release cadence.

- Developed product marketing strategy, establishing 4 strategic partnerships with institutions and selection for CES 2021.

- Raised funds and managed the budget to deliver the science and product.

- Analyzed competition to define the short-term product development and marketing tactical plan.

- Reduced manual analysis of fraudulent bank transactions by 15%. Designed AI and ML algorithm strategy and prioritized their development using the Lean AI methodology.

- MVP released in 6 months for test users. Expanded active user base to over 300 internal users.

- Managed a team of data scientists to deliver the AI solution using the product technical roadmap I implemented.

- Reported to senior management to establish the roadmap, budget, and KPIs, and kept them updated on progress.

- Developed a research and development plan for the next two years, including necessary human and financial resources.