About the job
About Us:
At Goodie, we empower leading brands to navigate the complexities of AI search. With billions relying on systems like ChatGPT, Perplexity, and Gemini for product discovery and purchasing decisions, it's crucial for brands to effectively manage and influence their online representation.
Our platform offers a comprehensive AI control plane, delivering real-time insights into brand narratives, competitor visibility, and an optimization engine designed to enhance performance. As pioneers in this emerging category, we are rapidly expanding, supported by esteemed investors and trusted by top-tier clients. We seek innovative, driven individuals to help us shape the future of AI search.
Your Role:
We are seeking a passionate and skilled Data Scientist to join our dynamic team at Goodie AI. In this role, you will be pivotal in transforming complex multi-model signals into actionable measurements, forecasts, and optimizations that drive our product strategies. If you thrive on building impactful models that influence customer behavior, this opportunity is for you.
Responsibilities:
- Manage and process large datasets, ensuring efficient querying, cleaning, labeling, and taxonomy alignment for brands, SKUs, and categories.
- Develop sampling and classification techniques to convert noisy LLM outputs and crawler logs into meaningful brand and product insights.
- Utilize LLMs and NLP to extract structured data from unstructured text on a large scale, focusing on topics like query fan-out, sentiment analysis, citation extraction, and entity linking.
- Establish product-grade metrics, creating clear definitions for visibility score, answer coverage, product presence, and agentic checkout readiness.
- Design and execute experimentation frameworks including A/B tests, holdouts, counterfactuals, and uplift modeling to measure impacts on citations, share of voice, and conversion rates.
- Build and refine predictive models to analyze and forecast behavior in AI search across different models and surfaces.
- Translate complex analytical findings into actionable insights, collaborating with the founding team to inform product roadmap, pricing, and customer engagement strategies.
- Create evaluation harnesses, implementing automatic evaluations and human-in-the-loop labeling for model quality, bias detection, and drift monitoring across LLM providers.
- Develop anomaly detection systems to monitor crawler behavior, rankings, and feed health, proactively identifying issues before they affect our customers.