Finance AI Leadership Director — Remote (US)

Dropbox; Wilmington (NC); Remoto; USD 203.000 - 309.000; Tempo integral

Resumo da vaga

Dropbox seeks a Director of Data Science & Data Engineering for Finance, leading a small team to deliver trusted data, robust analytics, and AI-powered finance capabilities. You will shape strategy, align with Finance leadership, and drive durable impact across forecasting and decision-support.

You will manage two direct reports (data scientist and data engineer) and partner with cross-functional stakeholders to transform ad-hoc requests into scalable, governed data products and reliable models.

Qualificações

• Bachelor's degree or above in a quantitative field or equivalent practical experience.
• Significant experience applying data science, analytics, or data engineering to business problems.
• Experience leading technical professionals and delivering projects end-to-end.

Responsabilidades

• Lead, coach, and develop a two-role data team (data scientist and data engineer).
• Translate Finance and company goals into a focused portfolio of work.
• Provide technical leadership across data science and data engineering and ensure production readiness.
• Advance AI and modeling capabilities within Finance workflows with proper governance.
• Build trusted data foundations and improve source-of-truth datasets and data quality.
• Own modeling outcomes and tie technical work to measurable business impact.

Conhecimentos

Data leadership

Finance domain knowledge

Stakeholder management

Formação

Bachelor's degree or above in a quantitative field

Ferramentas

Python

SQL

Spark

Descrição da vaga

Dropbox seeks a Director of Data Science & Data Engineering for Finance, leading a small team to deliver trusted data, robust analytics, and AI-powered finance capabilities. You will shape strategy, align with Finance leadership, and drive durable impact across forecasting and decision-support.

You will manage two direct reports (data scientist and data engineer) and partner with cross-functional stakeholders to transform ad-hoc requests into scalable, governed data products and reliable models.