### Role Description At Dropbox, people are our greatest asset. The People Analytics team partners closely with leaders across the company to help them make better, data-informed decisions about how we identify, attract, develop, and retain top talent. As Dropbox continues to scale and evolve its Talent Acquisition strategy, we’re looking for a Data Analyst who is passionate about problem-solving and using data to shape how we hire. In this role, you’ll partner deeply with Talent Acquisition, People Partners, and business leaders to analyze hiring data, uncover trends, and surface insights that influence workforce planning, recruiting strategy, and candidate experience. You’ll work across quantitative and qualitative data to understand what drives successful hiring outcomes, where bottlenecks exist, and how we can improve efficiency, quality, and equity in our hiring processes. You should have a demonstrated ability to think analytically about the business, translate ambiguous questions into structured analyses, and deliver clear, actionable insights. Success in this role requires strong attention to detail, high standards for data quality, and the ability to communicate findings in ways that drive real decisions. ###

Responsibilities

- Partner on analytics initiatives to understand and improve the effectiveness, efficiency, and quality of hiring across Dropbox. - Create clarity from ambiguity, bringing structure to complex data and stakeholder narratives to identify the underlying question, establish analytical rigor, and drive actionable conclusions. - Monitor and analyze core Talent Acquisition metrics, proactively identifying trends and uncovering the“what” and“why” behind changes in performance. - Build strong relationships with key stakeholders; lead

requirements

gathering and translate business questions into clear analyses and insights that inform People and business leader decisions. - Answer complex business questions through independent investigation and data forensics, leveraging the data warehouse to deliver timely, high-impact insights. - Uphold high standards for data quality and consistency by validating data, standardizing definitions and calculations, and contributing to shared data toolkits and enablement materials. - Ability to treat employee experience as a product, applying product management and design thinking to understand needs, prototype solutions, and drive execution through strong project management and data-driven iteration. ###

Requirements

- BA/BS in an analytical or quantitative field such as Industrial/Organizational Psychology, Mathematics, Statistics, Data Science, Engineering, or a related discipline. - 3+ years of experience in an HR-focused, stakeholder-facing Data Analytics role, with at least 1 year of experience focusing on Recruiting/Talent Acquisition insights. - Fluency in SQL and advanced Excel; experience using statistical or analytical tools such as R or Python. - Strong storytelling skills with data, including the ability to select appropriate analytical approaches and visualization techniques for different audiences and decision contexts. - Proven ability to analyze large, complex datasets, synthesize insights quickly, and communicate clear, actionable recommendations. - Demonstrated experience driving analytics projects end to end, from problem framing and analysis through to execution and impact. - Demonstrated experience leveraging AI tools in the flow of work. Candidates with a pre-existing comfort level & familiarity using AI to enhance productivity are strongly preferred. - Ability to think creatively and critically and thrive in a fast-paced, multifaceted, and often ambiguous environment. - Collaborative, humble team player who proactively supports teammates and shared goals. - Demonstrated ability to conceptualize employee experience as a product, with proven success applying product management principles(roadmapping, user journeys, feature prioritization) to HR initiatives - Proficiency in leveraging design thinking methodologies to deeply understand employee needs, rapidly prototype experience solutions, and implement data-driven iteration cycles that measurably enhance engagement and retention ###