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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - AI & Experimentation - **Company:** Plush Freight Logistics LLC - **Location:** United States (Remote available) - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, JIRA, Python (Programming Language), Machine Learning, NumPy, SQL Databases, Large Language Models, Pandas, Scikit Learn, Information Technology - **Published:** August 24, 2026 - **Apply:** https://arc.dev/remote-jobs/j/redirect/pelcxpzo6b ## About the Role * You love to work with data: explore it, model it, improve its quality. * Deep grounding in statistics: you know which method fits which problem and can defend your assumptions, not just run the library defaults * Fluent in Python (pandas, scikit-learn, NumPy) and SQL, with a track record of applying them to real business problems rather than toy datasets * Hands-on experience taking ML and modern AI techniques from idea to a working solution that someone actually uses * Practical experience with LLMs and RAG systems in production or near-production settings, including prompting, retrieval quality, and output evaluation * Solid command of A/B testing: sample sizing, significance, common pitfalls, and knowing when an experiment is the wrong tool * Working knowledge of performance marketing concepts such as CAC, ROAS, and attribution logic * Project experience in at least one of: anomaly detection, trend analysis, marketing mix modeling, or multi-touch attribution * Background in e-commerce, marketplaces, or other platform-based businesses, ideally with exposure to supply and demand dynamics * Bonus: degree in mathematics, statistics, physics, computer science, or a related quantitative field ## Description We're looking for a Data Scientist who treats AI as a working tool, not a buzzword. You'll sit at the intersection of statistics, machine learning, and product: building predictive models, improving our LLM- and RAG-based systems, and running experiments that directly shape how our platform matches supply and demand. Your work won't end at a slide deck. You'll define the metrics, ship the analysis, and follow through until the impact shows up in the numbers. Tasks * Build, validate, and ship statistical and predictive models that directly inform pricing, matching, and growth decisions * Develop and improve LLM-powered features, from retrieval-augmented generation (RAG) pipelines to applications of new AI technologies that open up product innovation * Own the reliability of our AI features: design prompt and evaluation workflows, measure output quality, and catch regressions before users do * Turn open questions into testable hypotheses and design experiments (e.g., A/B tests) that give clear, decision-ready answers * Dig into funnels and user journeys to find drop-offs and friction points, and quantify where supply and demand can be better matched * Team up with performance marketing to sharpen targeting, attribution, and campaign efficiency with data * Define the KPIs that matter, build the dashboards and monitoring behind them (AWS QuickSight), and make business impact visible and measurable * Keep your work transparent and traceable: document, prioritize, and communicate progress in Jira across product, engineering, and marketing * Present findings to stakeholders as concrete recommendations, then stay involved until they're implemented ## Related Videos - [Improving quality with Agentic AI with Rovo Dev and Xray](https://www.wearedevelopers.com/videos/2005-improving-quality-with-agentic-ai-with-rovo-dev-and-xray) - [Vectorize all the things! Using linear algebra and NumPy to make your Python code lightning fast.](https://www.wearedevelopers.com/videos/562-vectorize-all-the-things-using-linear-algebra-and-numpy-to-make-your-python-code-lightning-fast) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Collaboration Quantified: Lessons from Open Source Developer Networks](https://www.wearedevelopers.com/videos/1422-collaboration-quantified-lessons-from-open-source-developer-networks) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)