Head of Data Science - Dubai - DISCOVERED

    DISCOVERED
    DISCOVERED Dubai

    3 days ago

    Description

    We're looking for a hands‑on Data Science leader with product/e-commerce experience and startup-build exposure—someone who can set strategy from scratch while remaining an IC, not a pure people leader or program director.

    This is a perfect role for someone ready to step up into leadership, hire a small team, and scale a practice to 5–10 people.

    What You Will Lead


    • Strategy & Leadership
    • Own and execute the data science strategy tied to growth KPIs (acquisition, activation, AOV, repeat rate, margin).
    • Build a roadmap balancing fast iteration with longterm foundations (feature store, realtime inference, experimentation).
    • Hire and develop a multidisciplinary DS/ML/MLOps team.
    • Customer Insights & Personalization
    • Deliver multiobjective personalization across web/app surfaces.
    • Build recommenders, search relevance, semantic search, and LTR models.
    • Pricing & Merchandising Science
    • Lead dynamic pricing, elasticity models, and competitive pricematching.
    • Optimize promotions, assortment, and attribute coverage.
    • Apply causal inference for pricing/promo impact.
    • Forecasting & Inventory Optimization
    • Build multilayer forecasting models for buying and replenishment.
    • Develop availability, stockout, returns/refund, and supply‑chain efficiency models.
    • Marketing Science & Experimentation
    • Own fullfunnel attribution, incrementality, and ROAS optimization.
    • Lead always‑on experimentation with rigorous guardrails.
    • Deliver LTV, CAC, churn, and audience segmentation models.
    • Agentic AI & Automation
    • Build real‑time agentic systems for merchandising, pricing, and operations.
    • Implement human‑in‑the‑loop workflows and feedback loops for continuous learning.
    • Catalog Quality & Trust
    • Apply CV/NLP for enrichment, duplication, attribute extraction, and size mapping.
    • Build fraud/abuse detection with explainability and review layers.
    • Data Platform, MLOps & Governance
    • Collaborate with Engineering to scale the lakehouse, feature store, and streaming ecosystem.
    • Implement mature MLOps (CI/CD, registries, canary/shadow deployments, monitoring).
    • Champion governance, privacy, and model risk practices.
    Qualifications

    • Master's or PhD in a quantitative field.
    • 12–15+ years applied DS experience (marketplace/e‑com preferred).
    • Demonstrated success shipping production ML that moved KPIs at scale.
    Technical Skills

    • Strong Python/R/SQL and deep expertise in ML, DL, NLP, forecasting.
    • Experience with TensorFlow/PyTorch, Spark/Hadoop, and cloud platforms (AWS/GCP/Azure).
    • Solid grounding in experimentation, causal inference, and statistical modeling.
    If you fit the brief of the role and have built a product or ecommerce business's data science platform from the ground up, then APPLY NOW

    #J-18808-Ljbffr

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