Ngân hàng ShinhanBank ★ 3.6

- Proactively propose, design, and be responsible for implementing data science solutions, closely coordinating with business units to solve highly applicable practical problems.
- Perform data analysis and mining, collect, clean, and process data from various sources to serve analysis.
- Perform in-depth analysis and exploration of big data, using statistical probability techniques, machine learning, deep learning, and GenAI to detect trends, hidden behaviors, and factors that drive customer actions, thereby building valuable insights and supporting business strategy proposals, product design, or appropriate campaigns, and making recommendations.
- Develop machine learning, deep learning models and GenAI applications to serve the following goals: churn prediction, cross/up-sell, customer segmentation, customer lifetime value prediction (CLTV), next behavior prediction and personalization of multi-channel customer experience
- Personalize customer experience, analyze data to improve products, services and optimize customer approach strategies.
- Regularly research, update trends, advanced techniques in the field of data analysis, machine learning/deep learning and/or GenAI and apply them to work.
- Proactively learn and test new technologies, frameworks and models to improve the efficiency of data and AI solution implementation at the bank
- Ability to guide junior specialists.
- Participate in supporting training and guidance for lower-level team members when assigned.
- Perform other tasks assigned by competent authority.

University degree or higher in related fields such as: Computer Science, Mathematics/ Applied Mathematics, Statistics, Data Science, Econometrics, Quantitative Finance, or fields related to data analysis and information processing.
- Over 6 years of experience in advanced analysis, developing machine learning/ deep learning models and/ or applying AI/ Gen AI to practical problems.
- Experience in processing, visualizing and interpreting data in a profound way, connecting with business needs and suggesting specific actions.
- Ability to guide or support other members in the team when deploying models or processing data.
- Mastering knowledge of statistical models, machine learning algorithms, deep learning and GenAI, and being able to evaluate, customize and optimize techniques for complex real-world problems.
- Proficiency in SQL, data analysis/modeling tools (R & Python, etc.), and specialized libraries for machine learning, deep learning and GenAI
- Understanding and being able to participate in implementing model development and operation processes, including data processing, training, evaluation, testing, deployment and monitoring of models.
- Being able to coordinate effectively with business units to represent problems, convert them into specific data analysis solutions with high application value and measurable effectiveness.
- Presentation skills, clear and coherent communication, able to present analysis results, models and insights to coordinating units.
- Good problem solving skills, able to approach analytical problems in a structural and logical manner.
- Banking experience is a plus