Data Scientist (Applied AI)

About Cohere Commerce Cohere Commerce is the leading AI-driven platform for retail sourcing and vendor evaluation, trusted by buyers, consultants, and investors across North America. Backed by top-tier investors with tens of millions in funding and partnered with major retailers like Target and Sprouts, we deliver real-time, validated insights that help the industry make smarter product decisions, streamline supply chains, and enhance the customer experience. As we continue to grow, you’ll play a foundational role in shaping the future of retail intelligence. The Role We are looking for a highly motivated Data Scientist (Applied AI) to bridge the gap between traditional data science and cutting-edge Generative AI. In this role, you won’t just be crunching numbers in a vacuum—you will be building the intelligent engines and AI agents that drive our platform forward. What You'll Do Build the Foundation: Design and build high-quality data pipelines by extracting, cleaning, and integrating multi-source retail data (e-commerce transactions, social media, supply chain, user behavior, and funding info). Develop Applied GenAI: Play a core role in developing LLM-powered applications. You’ll build RAG (Retrieval-Augmented Generation) systems, manage vector databases, and continuously iterate on Prompt Engineering. Architect AI Agents: Help design and implement AI Agent workflows. You will use function calling and multi-step reasoning to automate complex, retail-specific business logic. Evaluate & Iterate: Write evaluation scripts to test model accuracy and prep datasets for fine-tuning, ensuring our models become leading "domain experts" in retail. Drive Business Value: Apply machine learning and statistical methods to power personalized recommendations and uncover deep insights into customer behavior. Ensure Data Integrity: Champion data governance, monitor data quality, and set up anomaly detection. You will also design and evaluate A/B tests to guide product decisions with hard data. What We're Looking For Required Education: Bachelor’s degree or higher in Computer Science, Data Science, Statistics, AI, or a related field. (Recent grads, current Master's/Ph.D. students, and early-career professionals with 1-3 years of experience are highly encouraged to apply!) Data Engineering Chops: Strong SQL skills with experience in massive data processing, ETL pipeline development, and an understanding of modern Data Warehouse/Data Lake architectures. Programming & ML: Fluency in Python. You are comfortable with data wrangling, feature engineering, and standard machine learning workflows (classification, clustering, evaluation metrics). LLM Foundations: You understand how Large Language Models work under the hood and have tinkered with frameworks like LangChain, LlamaIndex, LLM APIs, and vector databases. Hacker’s Mindset: You are highly self-directed. You can read documentation, quickly pick up new open-source tools or protocols (like MCP), and creatively solve engineering roadblocks. Analytical Rigor: You have a sharp sense for data, strong logical reasoning skills, and experience with hypothesis testing, A/B testing, and metrics management. Collaboration: Excellent communication skills with the ability to work cross-functionally and turn data into actionable business insights. Bonus If You Have Previous data project experience in retail, CPG, or e-commerce. Familiarity with managed AI services on AWS or GCP. Hands-on, demonstrable experience building RAG pipelines or AI Agents from scratch. Why You’ll Love It Here Full-Stack AI Impact: You will get hands-on experience across the entire AI lifecycle—from raw, underlying data pipelines to top-level AI Agent applications. Global Scale: You will tackle the industry's toughest challenges using real-world data from top-tier North American retailers. Massive Growth Potential: We are a fast-moving, flat-structured startup. Your code, your models, and your ideas will directly shape the product and the industry. Snacks and Products: Unlimited access to the latest unreleased snacks, drinks, beauty and more.