Data Scientist

a. ML Platform Development & Operations

• Deploy and operate ML Platform systems, including data ingestion, feature engineering, model training and serving.
• Build and maintain automated ML pipelines using Prefect/Airflow and MLflow.
• Package models with Docker, deploy to production and monitor model performance/drift.

b. Business Forecasting & Predictive Modeling

• Develop Churn Models to identify customers at risk of becoming inactive.
• Build Propensity Models to predict customer behaviors and optimize conversion rates.
• Perform Customer Segmentation to support personalized marketing campaigns.

c. AI Applications & Chatbot Development

• Apply RAG and Prompt Engineering to improve chatbots and internal AI assistants.
• Develop Agentic Workflows to automate and optimize business processes.
• Integrate AI into CRM systems to enhance customer management and personalization.
• Optimize chatbot processing and response logic to improve customer interactions.

• Bachelor’s degree in Mathematics, Computer Science, IT, Econometrics or related fields.
• 2+ years of experience as a Data Scientist or AI Engineer.
• Strong knowledge of Statistics, Machine Learning and Predictive Modeling.
• Proficiency in Python, SQL and ML libraries such as Scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch/TensorFlow.
• Experience with MLOps: MLflow, Airflow/Prefect, Docker, MinIO and model deployment.
• Knowledge/experience with LLMs, RAG, Prompt Engineering, LangChain/LlamaIndex/LangGraph is a strong advantage.
• Knowledge of Apache Spark, Kubernetes and AI Agent development is a plus.
• Experience in Finance, Securities or Banking is preferred.
• Strong analytical, problem-solving and Product Mindset.
• TOEIC 500 or IELTS 5.5

1. Preferred Qualifications * Experience building AI Agents / Agentic Workflows. * Experience developing AutoML / internal ML platforms. * Experience integrating AI with CRM, Marketing Automation or CDP. * Experience with OpenAI, Claude, Gemini and fine-tuning techniques such as LoRA/QLoRA/PEFT. * Knowledge of Securities products, investor behavior and KYC/AML.

• 5-day working week, Monday-Friday.
• Professional, dynamic working environment.
• Career development and training opportunities.
• Opportunity to work on large-scale data, AI and enterprise data modernization projects.
• Competitive benefits including insurance and health insurance.
• Salary: Negotiable.