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# Senior Data Scientist

- **Company:** Akaasa Technologies
- **Location:** Deerfield Beach, FL, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Big Data, Cloud Computing, Computer Programming, Graph Database, Mobile Application Software, Python (Programming Language), Machine Learning, Recommender Systems, Data Streaming, Reinforcement Learning, Large Language Models, Snowflake, Apache Spark, Deep Learning, Machine Learning Operations, Stream Processing, Databricks
- **Published:** June 4, 2026
- **Apply:** https://www.careerjet.com/jobad/usc0f90a10b08ed2d9f351fe297c22682e

## About the Role

* 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.

## Description

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


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