עדיין מחפשים עבודה במנועי חיפוש? הגיע הזמן להשתדרג!
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
מלאה
25,000-35,000 ₪
Were looking for a Senior Data Scientist to take full ownership of high-impact ML problems within our DSP platform.
You will work on core bidding, budget optimization, and prediction systems that operate at massive scale and strict latency constraints. This role combines deep modeling expertise, experimentation rigor, and strong product intuition.
You will be expected not only to build models - but to define problems, challenge assumptions, and drive measurable business impact.
What Youll Do:
Own end-to-end ML projects: problem definition → research → modeling → offline validation → production deployment → online A/B testing → impact analysis.
Develop and improve models for: Bid optimization , Conversion rate / pLTV prediction, Budget pacing and allocation, Auction dynamics & win-rate modeling.
Analyze large-scale, high-dimensional auction and user-level datasets to extract actionable insights.
Design robust feature engineering pipelines across behavioral, contextual, and advertiser-level signals.
Improve model performance under real-time constraints (low latency, high throughput).
Lead experimentation design and statistical validation of online tests.
Collaborate closely with engineering and product to translate research into scalable production systems.
You will work on core bidding, budget optimization, and prediction systems that operate at massive scale and strict latency constraints. This role combines deep modeling expertise, experimentation rigor, and strong product intuition.
You will be expected not only to build models - but to define problems, challenge assumptions, and drive measurable business impact.
What Youll Do:
Own end-to-end ML projects: problem definition → research → modeling → offline validation → production deployment → online A/B testing → impact analysis.
Develop and improve models for: Bid optimization , Conversion rate / pLTV prediction, Budget pacing and allocation, Auction dynamics & win-rate modeling.
Analyze large-scale, high-dimensional auction and user-level datasets to extract actionable insights.
Design robust feature engineering pipelines across behavioral, contextual, and advertiser-level signals.
Improve model performance under real-time constraints (low latency, high throughput).
Lead experimentation design and statistical validation of online tests.
Collaborate closely with engineering and product to translate research into scalable production systems.
Requirements:
4+ years of hands-on experience in Data Science / Machine Learning in production environments.
Proven track record of shipping ML models that created measurable business impact.
Experience in real-time systems, online experimentation, or large-scale optimization problems.
Technical Skills:
Strong Python skills with ML stack (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow).
Advanced SQL and experience working with large-scale datasets.
Deep understanding of:
Supervised learning (classification/regression)
Model evaluation & calibration
Feature engineering at scale
Hyperparameter tuning & regularization
Strong statistical foundation and experimental design knowledge.
Advantage (Highly Preferred):
Experience in AdTech / DSP / RTB environments.
Knowledge of auction theory or bidding strategies.
Experience with large-scale distributed data systems (Spark, Airflow, etc.).
4+ years of hands-on experience in Data Science / Machine Learning in production environments.
Proven track record of shipping ML models that created measurable business impact.
Experience in real-time systems, online experimentation, or large-scale optimization problems.
Technical Skills:
Strong Python skills with ML stack (NumPy, Pandas, Scikit-learn, PyTorch/TensorFlow).
Advanced SQL and experience working with large-scale datasets.
Deep understanding of:
Supervised learning (classification/regression)
Model evaluation & calibration
Feature engineering at scale
Hyperparameter tuning & regularization
Strong statistical foundation and experimental design knowledge.
Advantage (Highly Preferred):
Experience in AdTech / DSP / RTB environments.
Knowledge of auction theory or bidding strategies.
Experience with large-scale distributed data systems (Spark, Airflow, etc.).
This position is open to all candidates.
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
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