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Niche recommender and search expertise reduces candidate pool despite moderate brand and mid-level seniority.
ML/NLP and recommender skills transfer across publishing, retail, and marketplaces, but specialization matters.
Mandatory 6+ years, production ML, search/ranking expertise, and generative AI governance raise filter strictness.
Lead development of AI-enabled discovery, ranking, and recommendation models to transform complex content and market data into actionable insights.
Own the full solution lifecycle including model building, deployment, monitoring, and maintenance for AI-enabled workflows.
Collaborate with business stakeholders and technical teams to create scalable, governed intelligence products and promote responsible, reproducible data science practices.
Minimum 6+ years experience in data science, machine learning, or applied research with leadership of complex analytical products.
Strong expertise in Python, SQL, and advanced techniques in search, ranking, recommendations, NLP, embeddings, or graph methods.
Proven experience deploying models into production environments using modular code, APIs, automated tests, Git, CI/CD, and cloud platforms.
Experience applying generative AI or foundation models with appropriate privacy, bias mitigation, explainability, and human oversight controls.
Experienced in advanced discovery systems such as vector databases, retrieval-augmented generation, multimodal models, or knowledge graphs.
Skilled at designing credible evaluation frameworks combining offline metrics, human judgment, experiments, and business outcomes.
Strong ability to communicate complex technical concepts to business and technical leaders and mentor other data scientists.