About the Team You'll Join The Data Analyst at Toss Bank is integrated into both the squad and DA chapter, functioning within a matrix structure. At Toss Bank, teams are organized into squads, consisting of 6-8 professionals including Product Owners, Designers, Developers, and Analysts, working autonomously like a startup. Data Analysts in the Toss community belong to the DA chapter, which meets every Wednesday to share insights on data analysis topics. The DA chapter comprises team members with 1 to 12 years of experience from diverse backgrounds, including finance, corporate, gaming, and e-commerce. Key Responsibilities You'll Undertake As a Data Analyst at Toss Bank, you will define business problems through data and identify optimal solutions to effect real change. Drive Data-Driven Decision Making: Go beyond merely extracting requested data by defining the 'real problems' behind business needs and formulating hypotheses. Validate hypotheses using appropriate methodologies, such as causal inference and A/B testing, to derive actionable insights. Create Reliable and Efficient Analytical Environments: Focus on developing reusable data structures that team members can utilize repeatedly, moving beyond one-time analyses. Establish data standards through data mart design and consistency validation that everyone can trust. Work Smart with Technology: Utilize cutting-edge technologies (AI, LLM, etc.) to enhance efficiency in repetitive tasks, allowing for a focus on more significant problem-solving. Proactively adopt new analytical methods and tools that can elevate productivity without being constrained by past practices. We Seek a Candidate Who: Can discern the essence of problems and proactively propose solutions that consider the impact on our team, company strategy, and business objectives. Understands complex business logic and can translate this into coherent SQL queries for structured data. Is adept in deep data analysis using tools like Python/R, capable of accurately interpreting experimental results based on statistical knowledge. Can communicate complex analytical findings in simple terms that non-experts can understand and persuade. Preferred Experience: Experience in constructing dashboards and analytical environments using tools such as Tableau or Amplitude is a plus. Prior involvement in service planning and log design stages is advantageous. Experience in leveraging new technologies (like AI) to enhance work processes is preferred. Resume Tips: Detail impactful projects you have worked on. Showcase the process of problem definition, hypothesis formulation, experimental design, validation, and results. Mention any experiences that led to deep user understanding through data analysis and actionable insights. Check if you have extensively utilized mobile service data analysis methods (LTV, AARRR, Cohort, Funnel, etc.).
Mar 9, 2026
