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At Competency Center Customer Experience we seek an experienced Data Scientist specializing in Generative AI. You will work hands-on with Machine Learning and Big Data technologies within the Adobe Marketing Cloud and third-party tools to build scalable machine learning data products and solutions. Your tasks Apply state-of-the-art algorithms relying on knowledge of statistical modeling, machine learning, and optimization to develop new data products or improve the performance/quality of existing products Build, evaluate, and optimize models that incorporate machine learning, artificial intelligence, and Generative AI Specialize in building data pipelines, developing machine learning models, and performing advanced analytics and statistical analysis Collaborate with internal and external stakeholders to understand business and insight goals, define a learning agenda, and identify relevant KPIs and diagnostics to pursue Cooperate with other data scientists and define project requirements including data sources, algorithms, and implementation Prepare and present compelling analytical presentations and effectively communicate complex concepts to marketing and business audiences Build expert knowledge of the various data sources brought together for audience segmentation solutions – survey/panel data, 3rd-party data (demographics, psychographics, lifestyle segments), media content activity (TV, Digital, Mobile), and product purchase or transaction data Requirements Experience with Adobe’s analytics tools (e.G. Adobe Analytics) and third-party SaaS tools (e.G. Databricks, R) At least 5 years of relevant work experience Familiarity with applying statistics and data science tools on large datasets Deep knowledge of supervised vs. unsupervised learning algorithms, including neural networks/deep learning, SVM, decision trees (bagging, random forests, boosting), clustering, regression, and dimensionality reduction techniques Expertise in model training approaches, hyperparameter tuning, tuning learning rates, and model evaluation approaches Extensive experience with data preparation (normalization, scaling, etc.) for modeling Proficiency in Python/R, APIs, LLMs, SQL (including techniques for writing efficient code over large datasets), and Power Automate, exposure to Spark/PySpark systems in a distributed computing environment Strong analytical skills and proven track record in deploying innovative SaaS solutions in the tech industry

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