Senior Data Scientist

Overall Vision

• The organization is building a customer intelligence and personalization platform

• Goal is hyper-personalized, real-time customer experiences across:

• Casino gaming
• Hotels
• Restaurants & cafes
• Mobile applications
• Websites and e-commerce

The initiative is not about building ML models for experimentation only, but about:

• Driving real customer experience improvements
• Increasing engagement, satisfaction, and long-term revenue
• Using intelligence to spend rewards more effectively, not necessarily less

Platform & Architecture Overview Core Platforms

• Snowflake

• Serves as the data foundation
• Houses offline data, historical customer profiles, and long-term analytics
• Stores offline feature data (e.g., long-term gaming, hospitality, behavioral history)

• Databricks

• Serves as the machine learning and real-time inference platform

• Hosts:

• Model training and experimentation
• Real-time inference workloads
• Online feature store
• Streaming data processing

• 5+ years of experience in Data Science, with a strong focus on personalization and recommendation systems.
• Expertise in machine learning, deep learning, and statistical modeling.
• Strong programming skills in Python.
• Experience with big data technologies such as Spark, Databricks, Snowflake or similar.
• Familiarity with cloud platforms like AWS, GCP, or Azure.
• Experience in deploying machine learning models at scale using MLOps best practices.
• Strong understanding of A/B testing, experimentation, and causal inference.
• Ability to work with large-scale datasets and real-time data processing.
• Hands-on experience working with Large Language Models (LLMs) for analytics, search, data interaction use cases or similar.
• Excellent problem-solving and communication skills.

Preferred Qualifications: * with knowledge graphs, reinforcement learning, or multiarmed bandits for recommendations.

• business acumen and experience translating business needs into AI solutions.