Senior Data Scientist

Location: Remote (Florida preferred, but will consider anywhere in U.S. depending on willingness to come to the South Florida office monthly/quarterly)

Contract Duration: Long-term contract

Job Description

We are seeking a Senior Data Scientist with extensive experience in building, optimizing, and deploying advanced AI systems (recommendation engines, personalization models, and LLM-driven data applications). The ideal candidate will be passionate about leveraging data science to create tailored customer experiences using machine learning, deep learning, and AI-driven methodologies.

Key Responsibilities

• Design, develop, and optimize recommendation algorithms (collaborative filtering, content-based, hybrid models, etc.).
• Build scalable personalization models that improve user engagement, retention, and conversion.
• Utilize real-time and batch-based machine learning approaches for recommendation systems.
• Leverage techniques such as embeddings, reinforcement learning, and deep learning.
• Lead the data science design of an LLM-based engine that enables users to query and interact with enterprise data stored in Snowflake using natural language (“talk to your data”).
• Develop semantic layers, embeddings, and retrieval strategies (e.g., RAG-style architectures) to translate user intent into accurate, governed data queries and insights.
• Partner with data engineering to ensure robust data modeling, feature availability, and performant access patterns in Snowflake.
• Develop A/B testing and experimentation strategies to measure the impact of personalization.
• Work closely with engineering teams to deploy models in production at scale.
• Collaborate with product, marketing, and analytics teams to align models with business goals.
• Stay up to date with the latest advancements in recommendation systems and AI, with a strong focus on applied LLMs and enterprise GenAI use cases.

Requirements

• 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

• Experience with knowledge graphs, reinforcement learning, or multiarmed bandits for recommendations.
• Strong business acumen and experience translating business needs into AI solutions.