Senior Data Scientist

6 days ago

Hanoi Capital Region, Vietnam Ngân hàng TMCP Đông Nam Á - SEABANK Full time $100,000 - $120,000 per year

The Mission

SeABank is scaling its Advanced Analytics capabilities to drive hyper-personalization for millions of customers. We are seeking a Senior Data Scientist who bridges the gap between complex algorithms and real-world banking revenue.

In this role, you will move beyond manual model training. You will leverage AutoML to accelerate experimentation and build robust MLOps pipelines to deploy Propensity, NBO (Next Best Offer), and NBA (Next Best Action) models at scale.

Key Responsibilities

  1. Advanced Customer Analytics (Propensity & Personalization)


• Propensity Modeling: Design and deploy high-precision models to predict customer likelihood to purchase (Credit Cards, CASA, Loans, Insurance) using comprehensive behavioral data.


• NBO & NBA Engines: Build recommendation systems (Next Best Offer / Next Best Action) to deliver the right message, to the right customer, at the right time across digital and physical channels.


• Customer Lifecycle AI: Develop models for Churn Prediction, Reactivation, and Uplift Modeling to optimize marketing spend and retention strategies for Retail and SME segments.

  1. AutoML & Efficiency Strategy


• Accelerated Modeling: Utilize AutoML frameworks (e.g., H2O, FLAML, AutoGluon, or custom wrappers) to rapidly benchmark baselines, select features, and tune hyperparameters.


• Standardization: Create reusable coding templates and libraries to reduce "Time-to-Model" for the broader data science team.

  1. MLOps & Model Lifecycle Management


• End-to-End Deployment: Move models from Jupyter Notebooks to production environments using Docker/Kubernetes.


• Model Monitoring: Implement monitoring solutions (detecting Data Drift, Concept Drift) to ensure model performance remains stable over time.


• CI/CD for ML: Collaborate with Data Engineers to build automated retraining pipelines using tools like MLflow, Airflow, or Kubeflow.

What We Are Looking For

Core Technical Skills:


• Experience: 3+ years in Data Science with a proven track record in Banking, Fintech, or E-commerce.


• Programming: Mastery of Python (Pandas, Polars, Scikit-learn) and SQL for complex data wrangling.


• Modeling Expertise: Deep understanding of Ensemble methods (XGBoost, LightGBM, CatBoost) and Classification/Regression problems.


• Business Solvers: Strong experience specifically with Propensity Scoring, Collaborative Filtering, and Segmentation.

Operational Excellence (The "Must-Haves"):


• AutoML: Experience using AutoML tools to streamline the modeling process is highly preferred.


• MLOps: Hands-on experience with model registry, versioning, and deployment tools (e.g., MLflow, Docker).


• Cloud & Big Data: Familiarity with AWS/GCP or Spark/Hadoop ecosystems is a plus.

Why This Role Matters


• Direct Impact: Your Propensity and NBO models will be the engine behind SeABank's marketing campaigns and sales strategies.


• Tech Freedom: We encourage the use of AutoML to remove repetitive tasks so you can focus on feature engineering and solving hard business problems.


• Innovation: Join a team that values production-grade code over research papers.

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