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mylo AI · Tel Aviv District, Israel

Data Scientist

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Data Scientist – Match Quality & Feedback Loops

The Vibe:

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.

Who You Are:

- 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.

Sound Like a Fit?

Send your CV to [email protected] with the role title in the subject line.

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