Data/AI Engineer

• Build scalable data infrastructure to source, clean, and process large datasets for evaluating thousands of brands efficiently.
• Unlock insights through rapid analysis to answer critical business questions and help users make informed purchasing decisions.
• Apply AI to real-world problems by developing agentic tools and leveraging LLMs to automate data collection, improve recommendation systems, and scale brand sustainability assessment.
• Collaborate across teams with Engineering and Product to understand systems, identify improvement opportunities, and scale solutions.

This role creates positive change by building intelligent systems that gather, analyze, and scale data to evaluate purchases and brands on sustainability, turning complex environmental data into clear, actionable insights that inform real people's choices in the real world.

• Technical foundation with proficiency in SQL, Python, and building data pipelines, with at least a few years of experience in fast-moving work environments.
• AI-forward mindset as an early adopter of GenAI tools, exploring how LLMs can transform workflows.
• Structured thinking with a methodical approach to problems, seeking new data sources, validating hypotheses, and building scalable systems.
• Bias for action, thriving in fast-paced, ambiguous environments, shipping valuable work quickly, and iterating as needed.
• Clear communication skills for gathering requirements, synthesizing information, and proactive communication in writing and conversation.
• Passion for sustainability, motivated by helping people make informed choices and holding companies accountable.

No specific benefits, compensation, perks, or salary mentioned in the description.

Commons is an award-winning app that helps people make sustainable spending choices by discovering climate-friendly brands and earning rewards on eligible purchases, backed by notable investors and recognized as a TIME100 Most Influential Company and Fortune Impact 20 company.