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 Saa S 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/Py Spark systems in a distributed computing environment
- Strong analytical skills and proven track record in deploying innovative Saa S solutions in the tech industry