Data Scientist - Match Quality & Feedback Loops

Mylo AI · telaviv

This is a high-impact, algorithm-focused Data Science role for a sharp ML practitioner who lives at the intersection of recommendation systems, user psychology, and feedback loops. As our Match Quality & Feedback Loops Expert, you will own the algorithmic core that powers meaningful connections on our platform. You are not here to just build models in isolation; you are here to continuous-tune evaluation metrics, solve cold-start and balance problems, and optimize real-time feedback loops that drive true user satisfaction, engagement, and long-term retention. What You'll Do Algorithmic Match Quality: Design, train, and deploy production ML/AI models for recommendation engines, candidate ranking, and personalization to maximize match quality and user satisfaction. Feedback Loop Optimization: Build and refine implicit and explicit feedback mechanisms (likes, messaging patterns, churn/retention signals) to continuously evolve algorithmic performance in real time. Metric Frameworks & Evaluation: Define and implement robust online and offline evaluation frameworks, moving beyond naive accuracy metrics to measure long-term ecosystem health, fairness, and engagement. Cold-Start & Liquidity Optimization: Develop innovative strategies to address cold-start problems for new users and balance marketplace liquidity across different geographic and demographic cohorts. Cross-Functional Collaboration: Work hand-in-hand with Product Managers, Data Engineers, and Core AI/ML teams to translate complex behavioral insights into actionable product features. What We're Looking For Data Science & ML Veteran : 4+ years of hands-on Data Science experience building recommendation systems, ranking models, or matchmaking algorithms in B2C/tech environments - Must. Recommendation & AI Expert : Deep theoretical and practical experience with collaborative filtering, graph neural networks (GNNs), reinforcement learning, or modern embedding-based retrieval techniques - Must. Production & Code Powerhouse : Strong proficiency in Python, SQL, and modern ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn), with experience deploying and monitoring models in production. Causal Inference & Experimentation : Proven track record of designing A/B tests, measuring causal impact in complex two-sided ecosystems, and handling feedback loop biases. Fluent Communicator : Native/Fluent English and Hebrew (written and spoken) with the ability to explain complex algorithmic concepts clearly to non-technical stakeholders - Must. Curious & Impact-Driven : A passionate problem solver who cares deeply about user outcomes and thrives in a fast-paced, iteration-heavy startup culture. Why Join Us This is a core opportunity to directly shape the foundational algorithm of a revolutionary AI-powered dating platform. Your models will directly dictate user happiness, real-world connections, and overall platform growth.

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