Teams at Placer.ai

Investigate data quality questions and customer-reported discrepancies using SQL, Python, Databricks, and analytical notebooks. Identify anomalies, root causes, and methodological limitations; design rigorous QA and validation processes; and collaborate with Data Science, Engineering, Product, and Commercial teams. Translate complex findings into clear business explanations, improve monitoring and data quality methodologies, and independently drive ambiguous investigations to resolution while verifying AI-assisted analyses.

Leads financial planning, forecasting, budgeting, and performance analysis across the company. Builds and improves financial models, analyzes KPIs and budget variances, partners with R&D, product, and business teams, strengthens financial controls, and provides insights that guide strategic decisions. The role also leads cross-functional projects and supports reporting and process improvements in a fully remote, high-growth SaaS environment.

Build and own Placer.ai’s first consumer mobile apps across Android and iOS, including scalable backend services, onboarding, consent and privacy flows, analytics, experimentation, fraud controls, and production reliability. Take the product from prototype through launch and growth, manage app-store submissions, integrate data collection technology, use AI-first development practices, and help hire and mentor the growing engineering team.