Senior Data Scientist (USA / Israel)

Master's or Ph.D. in Computer Science, Statistics, Applied Mathematics, Economics, Physics, or related discipline. 5+ years of experience deploying models in a professional setting. Strong experience building and deploying predictive models and recommendation systems. Deep experience with various machine learning techniques (regression, classification, clustering, etc.). Familiarity with algorithms like decision trees, random forests, Boosted trees, and regularized regression. Experience with match-propensity models, embeddings based models, cold-start handling, calibration/post-processing. Experience integrating models into ad-tech workflows and business logic. Experience measuring model performance within ad-tech systems. Solid foundation in statistical concepts, linear algebra, calculus, and probability theory. Proficiency in Python or R, and libraries like NumPy, Pandas, or SciPy. Solid understanding of data preprocessing, feature engineering, and model evaluation. Experience in ad-tech, media/advertising platforms, DSPs, SSPs, or retail-media networks. Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus. Excellent problem-solving and critical thinking skills. Excellent communication and collaboration skills.

Explore and analyze large datasets to identify patterns and gain insights for modeling. Design and develop predictive models and recommendation systems using statistical and machine-learning techniques. Prepare data for modeling, including gathering, integrating, and ensuring quality. Evaluate and test model performance using appropriate metrics. Optimize and tune models to improve accuracy and efficiency. Design, build, and evaluate systems for personalizing consumer experiences. Collaborate with cross-functional teams to translate business requirements into data-driven solutions. Monitor model performance and refine models based on new data. Stay updated on advancements in data science and machine learning.