Role DescriptionHow many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As a Senior Data Scientist for this new division, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business. Joining on the ground floor of this startup team, you’ll partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way! Responsibilities - Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth - Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies - Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques - Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written - Identify what matters most and prioritize ruthlessly for the area you will own - Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact - Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate Requirements - Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field - 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company - Proven track record of being able to work independently, driver measurable business impact, and proactively engage with business stakeholders with minimal direction - Proficiency in SQL, Python or other programming/scripting languages - Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees - Ability to provide data insights and recommendations for 0→1 product even when sample size is small - Strong verbal and written communication skills Preferred Qualifications - Experience in startups or building 0→1 products - Expertise in using data to inform AI/ML product development - Background in SaaS product Compensation US Zone 1 This role is not available in Zone 1 US Zone 2 $173,700—$234,900 USD US Zone 3 $154,400—$208,800 USD

• Lead complex analyses that answer high-impact business and product questions, using strong statistical thinking, modeling, and sound analytical judgment. • Create clear approaches to ambiguous problems by defining the right methodology, identifying the required data, and delivering actionable insights that drive decision-making. • Assess the business impact of product changes, recommendation systems, experiments, and other strategic initiatives, including ROI, forecasting, and performance measurement. • Work closely with Product, Engineering, and other cross-functional partners to shape priorities, influence decision-making, and communicate findings clearly and compellingly. • Mentor other analysts through technical guidance, collaboration, and shared best practices that raise the quality of analytics across the team.

CAPCO POLANDTRINITY GAMECapco at Data & AI Warsaw Tech Summit 2026 Capco drives digital transformation across the financial industry. A global consulting firm focused on financial services, Capco partners with leading banks, fintechs, and financial institutions to design and deliver next-generation data platforms, AI solutions, and digital ecosystems. From data strategy and modern platforms to AI-powered decision systems and GenAI innovation, teams unlock measurable value from data. What defines Capco? A fast, flexible, and entrepreneurial environment. Quick decision-making, creative thinking, and real ownership enable people to push the boundaries of what technology can achieve. Capco stands for: • Trusted partnerships with banks, payments providers, and financial institutions • Delivery of modern data platforms and AI-powered systems • Innovation across cloud, data engineering, machine learning, and GenAI • A community of engineers, architects, and consultants solving complex challenges Meet Capco at the Data & AI Warsaw Tech Summit 🚀At this year’s Data & AI Warsaw Tech Summit, Capco will share how financial institutions can move from experimentation to production-grade AI and scalable data ecosystems. Our experts will explore how organizations can: • Build AI-native architectures on modern cloud platforms • Scale machine learning and generative AI solutions across enterprise environments • Transform fragmented data into high-value data products • Embed AI into real business workflows and decision-making systems Capco Speakers at Data & AI Warsaw Tech Summit 🚀Andrzej Worona & Laura Żusin-Kaczmarek Topic: From Data to Meaning: Educating AI in Banking with Ontologies: Lessons from FIBO and Conversational Banking Time: 11:50-12:10 CET Intro: Many AI solutions still fall short when it comes to understanding and reasoning about complex financial concepts. The real challenge is about how financial knowledge is represented and shared with machines. Why does AI still misunderstand basic banking terms despite having access to vast amounts of data? How can AI truly understand financial concepts? Using the Financial Industry Business Ontology (FIBO) as an example of structured domain knowledge, we will discuss how formal, machine-readable definitions can provide the contextual foundation AI needs. By analysing selected conversational banking scenarios and example solutions, we will invite participants to reflect together on what the right semantic layer for AI in banking should look like. Join us to discover why the next leap in AI for banking isn’t just about more data or better models, but about building a structured understanding of financial meaning. WELCOME TO TRINITY GAME

• Perform various analyses to understand data sources and generate business insights; • Develop statistical models using different techniques; • Continuously refine and improve developed statistical models; • Monitor the performance of production statistical models; • Act as a technical reference for other professionals in the team; • Support the technical development of new business requirements; • Lead research projects aimed at opening new avenues in data analysis; • Create high-impact Data Science projects; • Present model results to business stakeholders to highlight the importance of model deployment, communicate obtained insights, and translate model outputs into business terms.