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Dropbox

Director, Data Science & Engineering, Finance

Dropbox

. Lead a small, high-impact team of a data scientist and a data engineer supporting Finance .

Posted 11/5/2026full-timeRemote • United StatesLead💰 $203,000 - $309,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data science and data engineering, with a strong focus on financial data quality, model development, and stakeholder communication. Proven ability to lead teams, manage projects, and influence business decisions through data-driven insights.

Highest-signal resume keywords
Data ScienceData EngineeringMachine LearningTeam LeadershipStakeholder Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Data ArchitectureData PipelinesModel DevelopmentData QualityAdvanced AnalyticsAutomationExperimentationMonitoringDocumentationTechnical Debt Management
Soft Skills
CoachingCommunicationGrowth MindsetProblem FramingInfluencing Business Decisions
Industry Keywords
FinanceQuantitative DisciplineOperational SupportKnowledge SharingTechnical Leadership

About the role

Key responsibilities & impact
  • Lead a small, high-impact team of a data scientist and a data engineer supporting Finance
  • Manage, coach, and develop team members through clear expectations, development plans, delegation, and ownership
  • Set team strategy and priorities across strategic initiatives, recurring operations, model maintenance, knowledge coordination, and technical debt
  • Provide technical leadership across data science and data engineering, including problem framing, modeling, data architecture, pipelines, testing, monitoring, documentation, and production readiness
  • Identify and establish standards for AI, machine learning, automation, advanced analytics, experimentation, evaluation, interpretability, human oversight, privacy, and monitoring
  • Improve financial data quality, lineage, observability, documentation, governance, and reliability
  • Ensure models and analyses support financial planning, forecasting, driver understanding, and decision-making
  • Establish operating mechanisms for intake, prioritization, roadmaps, reviews, incident response, documentation, knowledge sharing, and stakeholder communication
  • Communicate data, model, and engineering implications, recommendations, risks, and trade-offs to technical, non-technical, Finance, and executive audiences
  • Partner with Finance, Engineering, Data, Product, software engineering, and executive stakeholders
  • Automate recurring tasks, improve service levels, and increase the team’s strategic contribution

Requirements

What you’ll need
  • Bachelor’s degree or above in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative discipline, or equivalent practical experience
  • Significant experience applying data science, machine learning, analytics, data engineering, or a combination of these disciplines to business problems
  • Experience directly managing and developing technical professionals, ideally including both data scientists and data engineers or closely adjacent roles
  • Strong professional foundation in either data science or data engineering, with demonstrated ability to work effectively across the other discipline
  • Experience leading a portfolio of projects from problem definition through delivery, adoption, measurement, and ongoing operation
  • Experience with data quality, data pipelines, analytical datasets, model development or maintenance, experimentation or evaluation, and production or operational support
  • Demonstrated ability to use data and technology to influence business decisions and deliver measurable impact
  • Strong communication and stakeholder-management skills, including the ability to explain technical concepts, uncertainty, and trade-offs to Finance and executive audiences
  • Demonstrated growth mindset: actively seeks feedback, learns new technologies and domains, adapts to changing conditions, and creates an environment where the team does the same
  • Ability to operate with a high degree of autonomy and ownership in an ambiguous, fast-changing environment