Data Scientist with Adobe tools

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