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Senior Data Scientist
PresencialTiempo completoData ScienceeCommerceEnterprise Software
Join a hands-on data science team developing production models for shopper identity, customer value, recommendations, personalization, and autonomous checkout decisioning across ecommerce merchants. This individual contributor role is based in the Tel Aviv office four days per week and offers scope,
Responsabilidades
- Develop shopper identity and confidence scoring across merchant checkouts.
- Build customer value models across the merchant network.
- Develop recommendation and personalization systems using cross-shop behavior.
- Own coupon and shipping-option decisioning and its learning loop at checkout.
- Select and defend modeling approaches, including machine learning, recommender systems, causal methods, and bandits.
- Build, deploy, and operate models in production across merchants with different catalogs, margins, and shoppers.
- Lead data science projects end to end and establish modeling standards for the team.
Requisitos
- At least 5 years of hands-on experience as a data scientist, machine learning engineer, or similar professional.
- At least two roles involving end-to-end ownership of production models.
- Depth in one or more of customer value modeling, recommendation systems, causal inference and uplift, bandits and reinforcement learning, or entity resolution.
- Ability to lead projects from scoping and trade-offs through deployment and production ownership.
- Knowledge of experimentation fundamentals and the ability to design reliable tests and evaluate offline estimates.
- Strong SQL and Python skills.
- Ability to explain modeling decisions in business language to non-specialists.
- Ability to work from the Tel Aviv office four days per week.
- Full professional proficiency in written and spoken English.
Se valora
- Experience in ecommerce or in software or services serving ecommerce businesses.
- Background in consumer psychology and business decision-making.
- Experience with entity resolution, identity graphs, or probabilistic matching at scale.
- Experience with bandits, off-policy evaluation, or reward attribution in live systems.
- Experience using embeddings or large language model representations in decisioning or personalization.
- Experience modeling under privacy or consent constraints.
- Experience serving models across customers with substantially different businesses.
- MSc or PhD in a quantitative field.
- Knowledge of Snowflake.