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# Data Scientist

- **Company:** YNAP Corporation
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Confluence, JIRA, Continuous Integration, Statistical Hypothesis Testing, Python (Programming Language), Linear Regression, Logistic Regression, Machine Learning, Microsoft Visual Studio, Object-Oriented Software Development, SQL Databases, Large Language Models, Software Application Programming, Generative AI, Git, Pyspark, Information Technology, Atlassian Tools, Production Code, Bitbucket, Machine Learning Operations, GPT, Databricks
- **Published:** July 14, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/p491f3wrb7

## About the Role

* Bachelor's or Master's degree in Math, Statistics, Computer Science or similar
 * 4+ years of professional experience (at least 5+ models in production delivering consistent business value)
 * Working knowledge of Databricks & MLflow, LLM frameworks (e.g., LangChain or LlamaIndex), and Vector databases and embedding models
 * Expert level in Python, SQL, and working knowledge of PySpark, GIT & CICD and Object-Oriented Programming
 * Experienced with Atlassian suite (Jira, Bitbucket, and Confluence) and PyCharm or Visual Studio
 * Strong foundation in key topics of statistics, including sample selection, probability, hypothesis testing, and linear regression.
 * Strong understanding of key machine learning algorithms, including logistic regression, decision trees, random forests, and clustering algorithms.

## Description

* As a Data Scientist at LuxExperience Group, you will be working with commercial and marketing business stakeholders to provide smart data automations and support their decision-making.
 * Train, deploy and monitor machine learning, recommendation and Generative AI models in production.
 * Work alongside software developers in building applications to service your data and models
 * Build production-grade code
 * Work with stakeholders throughout the business to encourage a data-driven approach through the delivery of automated data products and accessible, actionable insight.
 * Identify opportunities to improve the efficiency of the Data Science team through improved work practices and the development of data assets.


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