Director, Data Science & Engineering, Finance

Dropbox is a Virtual First company. For this role, we are hiring in Zones 2 and 3. Zones are determined by your zip code; if you’re within 100 miles of a listed metro area (straight-line radius), you’re included in that Zone. Please check your Zone in the Compensation section below.

Role Description

This is a critical leadership role at the intersection of data science, data engineering, finance, and AI. As Director, Data Science & Data Engineering for Finance, you will lead a small, high-impact team that enables Finance to make better decisions through trusted data, robust analytical systems, applied modeling, and increasingly AI-powered capabilities.

You will manage two direct reports: a data scientist and a data engineer. Together, the team supports the financial organization across recurring business operations, driver-model maintenance, knowledge coordination, analytical insights, and the development and operationalization of AI and machine-learning use cases. The role requires enough technical depth to guide both disciplines, while maintaining a clear focus on business outcomes, reliability, and team growth.

You will partner closely with Finance leadership, Engineering, Data, Product, and other cross-functional stakeholders to establish priorities, improve the quality and accessibility of financial data, and shape a forward-looking roadmap. You will be expected to move the team beyond request-driven execution: identifying the highest-leverage opportunities, clarifying the problems worth solving, and creating the operating mechanisms needed to deliver durable impact.

This is an opportunity to shape how Finance uses data and AI at a time when the underlying technologies, operating models, and expectations are changing quickly. The successful candidate will bring a growth mindset, a strong background in either data science or data engineering, and the ability to lead effectively across both disciplines.

Responsibilities

Manage and grow a multidisciplinary team: Lead, coach, and develop a data scientist and a data engineer, creating clear expectations, meaningful development plans, effective delegation, and a strong culture of ownership and continuous improvement.
Set the team’s strategy and priorities: Translate Finance and company goals into a focused portfolio of work. Prioritize ruthlessly across strategic initiatives, recurring operational responsibilities, model maintenance, knowledge coordination, and technical debt.
Provide technical leadership across data science and data engineering: Guide problem framing, analytical and modeling approaches, data architecture, pipeline quality, testing, monitoring, documentation, and production readiness. You do not need to be the deepest expert in both disciplines, but you must be able to ask the right questions, recognize trade-offs, and raise the technical bar.
Advance AI and modeling capabilities: Identify high-value opportunities to apply AI, machine learning, automation, and advanced analytics to Finance workflows. Establish appropriate standards for experimentation, evaluation, interpretability, human oversight, privacy, and ongoing monitoring.
Build trusted data foundations: Partner with data engineering and Finance stakeholders to improve source-of-truth datasets, data quality, lineage, observability, documentation, and reliability. Ensure that recurring reporting, driver models, and downstream analyses are based on accurate and well-governed data.
Own analytical and modeling outcomes: Ensure the team develops, maintains, evaluates, and improves models and analyses that support financial planning, forecasting, business-driver understanding, and decision-making. Connect technical work to measurable business outcomes rather than treating model delivery as the finish line.
Create scalable operating mechanisms: Establish lightweight processes for intake, prioritization, roadmap planning, model and pipeline reviews, incident response, documentation, knowledge sharing, and stakeholder communication. Reduce dependency on individual heroics and make the team’s work easier to understand and extend.
Influence Finance and senior stakeholders: Communicate complex data, model, and engineering considerations clearly to technical and non-technical audiences. Present implications, recommendations, risks, and trade-offs in a way that enables timely decisions.
Partner across functions: Work effectively with Finance leaders, analysts, data scientists, data engineers, software engineers, product partners, and executives. Seek diverse perspectives, lead productive debate, and align stakeholders when priorities or approaches differ.
Improve the team’s scope and effectiveness: Look continuously for ways to eliminate low-value work, automate recurring tasks, improve service levels, and increase the team’s strategic contribution. When the current operating model is insufficient, make the case for change and lead the team through it

Requirements

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.
A 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.

Preferred Qualifications

Experience supporting Finance, financial planning and analysis, forecasting, corporate strategy, accounting, or other business functions with high standards for accuracy and control.
Experience building or scaling AI/ML capabilities, including generative AI, predictive modeling, model evaluation, workflow automation, or AI-assisted decision support.
Experience managing a hybrid or multidisciplinary team spanning data science, analytics, data engineering, or software engineering.
Experience building 0-to-1 capabilities, establishing new operating models, or transforming a team from reactive execution to proactive partnership.
Experience with data governance, observability, model risk management, responsible AI, or other practices that support reliable and auditable business decisions.
Experience working in a technology company or other complex, data-rich environment.

Durable Skills

AI fluency means using these tools to amplify human judgment, not replace it. We believe people with these skills will thrive as work and technology continue to evolve:

Awareness: Understand yourself and others.
Judgment: Evaluate information and make decisions in complex situations.
Adaptability: Learn, adjust, and stay effective through change.
Connection: Communicate, collaborate, and build trust.

To learn more about why these skills matter and what the data shows about thriving through change, read this blog post from our Chief People Officer, Melanie Rosenwasser.

Compensation

US Zone 1

This role is not available in Zone 1

US Zone 2

$228,400—$309,000 USD

US Zone 3

$203,000—$274,600 USD

The range(s) listed above is the expected annual salary/OTE (On-Target Earnings) for this role, subject to change. Please note, OTE are for sales roles only.

Salary/OTE is just one component of Dropbox’s total rewards package. All regular employees are also eligible for the corporate bonus program or a sales incentive (target included in OTE) as well as stock in the form of Restricted Stock Units (RSUs).

Dropbox takes a number of factors into account when determining individual starting pay, including job and level they are hired into, location/metropolitan area, skillset, and peer compensation. We target most new hire offers between the minimum up to the middle of the range.

Dropbox uses the zip code of an employee’s remote work location to determine which metropolitan pay range we use. Current US Zone locations are as follows:

US Zone 1: San Francisco metro, New York City metro, or Seattle metro
US Zone 2: California (outside SF metro), Colorado, Connecticut (outside NYC metro), Delaware, Illinois (Chicago metro), Indiana (Chicago metro), Maryland, Massachusetts, Michigan (Chicago metro), New Hampshire, New Jersey (outside NYC metro), New York (outside NYC metro), Oregon, Pennsylvania (D.C. metro), Pennsylvania (outside NYC metro), Texas (Austin metro) Virginia (DC metro), Washington (outside Seattle metro), Washington DC metro, West Virginia (DC metro), Wisconsin (Chicago metro)
US Zone 3: All other US locations

Check Your Zone

Company Description

Dropbox isn’t just a workplace—it’s a living lab for designing a more enlightened way of working. We’re a global community of bold visionaries and resourceful doers shaping the future of Dropbox and, in turn, the future of work. Our Virtual First model combines the autonomy of a distributed workplace with the power of human connection, creating space for meaningful work and lasting relationships. With a startup mindset and enterprise-level opportunities, we expect Dropbox employees to think critically, stay curious, and use modern tools, including AI, to improve how work gets done. Here, you can be who you are and grow into who you’re meant to be. You own your impact, helping make work more intuitive, joyful, and human for yourself and hundreds of millions of people worldwide. If you’re ready to push boundaries and challenge yourself, Dropbox is ready for you.

Team Description

The Dropbox Finance Team creates the financial infrastructure that powers our growth and scales our business. We combine analytical precision with bold thinking to build sustainable value for our company and stakeholders. More than traditional accountants, auditors, and finance managers, we're strategic partners who craft the financial architecture that enables innovation. Working closely with internal teams and external partners, we continuously look for ways to drive business impact while maintaining trust, accuracy, and rigor in everything we do. If you're ready to own your impact on Dropbox’s financial future, join our Finance team.

Virtual First

Dropbox’s Virtual First way of working is designed to help people do their best work with flexibility, autonomy, and connection. Day to day, teams work remotely with nonlinear schedules and core collaboration hours that support deep focus and individual working styles. We prioritize asynchronous communication to improve clarity, respect deep work time, and reduce unnecessary meetings. While remote work is the primary experience for our employees, we also prioritize intentional, in-person connection. We bring teams together through regular team gatherings, on-demand workspaces, and Dropbox Neighborhood events in order to strengthen team cohesion, foster creativity, and enhance momentum. Virtual First is built to provide the same access to opportunity, growth, and impact for everyone, regardless of location.

This role requires travel to offsites and various other team gatherings (approximately 5-10% of the year or 2-3 days per quarter). We provide advance notice when possible and encourage candidates to discuss any accommodation needs during the interview process.

AI Fluency

AI fluency is a core part of how we work and grow. It’s not about being an expert—it’s about using these tools thoughtfully and effectively to improve your work and support others.

We look for four key behaviors in candidates:

Ownership: You use AI responsibly by protecting data, applying sound judgment, and taking accountability for the quality and accuracy of your work.
Experimentation: You explore new AI capabilities and apply them to improve workflows within approved tools and practices.
Leverage: You use AI to enhance thinking, improve efficiency, and increase your impact and your team’s.
Learning: You stay current on emerging AI tools and trends, continuously build your skills, and share what you learn with others.

Together, these behaviors help build a workforce where technology amplifies human judgment, creativity, and impact.

Dropbox supports responsible use of AI for preparation, but misrepresentation of skills or experience is not permitted. To learn more, see our approach to AI in hiring.

Dropbox is an equal opportunity employer. We are a welcoming place for everyone, and we do our best to make sure all people feel supported and connected at work.