Bank Salad enriches users' lives through data services.
The mission of Bank Salad is to create an environment where users can utilize their information anytime and anywhere, designing digital experiences that maximize user benefits. We particularly focus on the important values of 'money' and 'health' for people.
I believe that a company that continuously produces products with innovative ideas is a startup.
We have proven our innovativeness by being the first in the country to launch products such as automatic accounting (2017), integrated financial inquiry (2018), consumption-based card recommendations (2018), loan comparison services (2019), credit score enhancements (2019), financial assistants (2020), my data (2022), free genetic testing (2023), customized health coverage analysis (2024), salad game (2025), and minimum interest rate alerts (2025).
In the last two years, our monthly revenue has grown by 800%, and we have surpassed monthly operating profit (BEP), securing sustainability and stability.
By expanding into finance based on the data synergy encompassing finance and health, we aim to become a digital finance holding company in 5 years and a data holding company that expands various businesses with information as a core asset in 10 years.
I want to work with colleagues full of challenge spirit who want to create a culture of solving problems without limits, together building processes that utilize data the safest, while generating tangible results in products and business.
Health PA specifically performs the following tasks:
The mission of Health PA is to gather scattered health data, connect it to personalized health care and insurance, creating a single solution. Although the digital healthcare market faces several challenges, such as regulation and low willingness to pay, the spread of healthcare and health my data and the increase in demand for health management present definite opportunities.
We offer health management services that motivate users to take action.
Simply showing health examination information, public my data, hospital APIs, etc., does not mean that we created a health management service. We focus not just on providing data, but on ‘motivating the user to actually take action’. We consider motivation systems beyond just providing health information (goal setting, notifications, challenges) and continuously create products that motivate action.
We offer easily usable examination services and focus on customer experience.
Bank Salad’s non-face-to-face genetic testing and microbial testing, the first to app-service all procedures in the country, lead to an easy and comfortable way to check and manage health status. More than 1 million people have accessed our non-face-to-face testing services, and over 300,000 have utilized the test results for health management. This level is greater than the total number of tests conducted by the entire genetic testing industry prior to the launch of Bank Salad’s genetic testing service. We are continually expanding the scale and scope of testing to create a world where health data can be checked and managed easily anytime and anywhere.
Furthermore, we offer solutions that integrate health and financial risk management.
Health issues can lead to financial burdens. We aim to provide solutions that help users easily find necessary coverages, optimize insurance premiums, and streamline the enrollment and claim processes. Specifically, we are enhancing services that predict individual disease occurrence based on comprehensive analysis of health examinations, genetic tests, and lifestyle data, recommending optimal insurance products based on this.
Additionally, to minimize negative experiences in insurance consultations, we are building a non-face-to-face consultation system to assist users in understanding and enrolling in insurance conveniently. Despite many challenges such as regulatory restrictions, we have ultimately achieved over 600% growth in the insurance business through multiple updates, training, and improvements.
The Data Analyst (Health) specifically performs the following tasks:
Analyzes GA (insurance consultants) counseling data to uncover key factors that enhance conversion rates, enabling users to receive optimal insurance consultation and proposes areas for improvement.
• Identifies high and low conversion counseling patterns based on counseling history data and quantifies key factors that affect conversion rates.
• Utilizes natural language analysis to extract meaningful patterns from counseling texts and derives effective counseling methods and scenarios.
• Derives actionable insights and presents strategies through cause analysis and hypothesis testing for businesses/products.
• Enhances understanding of products by analyzing and modeling health and insurance-related behavior data of Bank Salad users.
Designs a measurement system to facilitate quick and accurate decision-making on counseling quality, defines key metrics, and leads experiments.
• Designs and implements key metrics that link to product growth.
• Designs event logs to track conversion performance by counselor and scenario and measures experiences.
• Processes and visualizes data to allow team members to easily understand and utilize metrics.
• Collaborates closely with health team PM/PA, and GA managers to reflect analysis results in counseling operations.
• Designs and builds data marts to enhance analysis efficiency.
Designs quasi-experiments to verify the causal effects of counseling methods and experimentally identifies counseling scenarios that yield higher conversion rates.
• Sets the counseling methods of consultants as controlled variables and designs and conducts quasi-experiments.
• Validates the statistical significance of experimental results and interprets causal effects for decision-making use.
• Designs and conducts A/B tests and verifies the statistical significance of experimental results.
Primarily utilizes the following tech stack (tools):
• Data processing and analysis tools: Snowflake, Metabase, Amplitude
• Natural language analysis: Python (pandas, scikit-learn, KoNLPy, etc.), LLM-based analysis
• Languages: Python, SQL
We want to embark on this journey with those who aspire to have this experience.
• Must have more than 7 years of data analysis experience or equivalent, leading analysis projects that influence product/growth decision-making.
• Must have experience managing large data sets using SQL and executing end-to-end tasks including key metric design, root cause identification, and strategy proposal.
• Should have the capability to explain user value and revenue contribution by combining an understanding of financial data structure with behavioral data.
• Must have experience using advanced analytical methodologies such as statistical modeling and machine learning techniques.
• Must have understanding and practical application experience of A/B testing and hypothesis testing (metric definition, experiment design, result interpretation).
• Must have communication/leading skills that structure problems based on data and raise the organization’s decision-making capabilities while collaborating with various occupations/leadership.
Preference will be given to those who possess this experience.
• Preference for those with experience in analysis automation/reporting and statistical and recommendation, classification, prediction modeling using Python or similar tools.
• It would be better if you have a Master’s/Ph.D. in Computer Science, Mathematics, Statistics, or Data Mining-related fields.
• Preference for those who have created clear business/user impact (revenue, retention, conversion, cost savings, etc.) through data analysis or modeling.
• Preference for those who have built or enhanced indicator, experiment, data quality/definition systems in organizations that make decisions based on data.
• It’s good to have experience in building data marts and designing data pipelines based on an understanding of data warehousing (DW).
• Preference for those who systemically perform experiment designs and possess technical capabilities in statistical hypothesis testing, along with interpretation skills considering causal/bias issues.
• It’s definitely a plus if you have experience leading junior analysts or establishing and disseminating guidelines within the team.
