Data Scientist - Expert

September 15

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Marketing services • Direct Marketing Agency • Digital agency • Information Technology • Marketing Technology

1001 - 5000

Description

• The Expert Data Scientist (Adobe Practice) will work hands-on with Machine Learning and Big Data technologies within the Adobe Marketing Cloud and third-party tools. • Responsibilities include collaborating with stakeholders to identify insight requirements and applying creativity to test hypotheses, prepare data, build models, analyze and visualize results, and integrate the solution into innovative data products. • Build expert knowledge of various data sources for audience segmentation solutions and work with Product and Engineering teams to transition development projects to production systems. • Prepare and present compelling analytical presentations to marketing and business audiences, providing mentorship where necessary.

Requirements

• Expert-level experience with Adobe’s analytics tools (e.g., Adobe Journey Analytics) and third-party SaaS tools (e.g., Databricks, R). • Experience 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. • Specialization in Generative AI. • Expert at model training approaches, hyperparameter tuning, tuning learning rates, and model evaluation approaches. • Extensive experience with data preparation (normalization, scaling, etc.) for modeling. • Proficient in Python/R, APIs, Excel, LLMs, SQL, and Power Automate. • Exposure to Spark/PySpark systems in a distributed computing environment. • SQL mastery, including techniques for writing efficient code over large datasets. • Ability to leverage critical data-driven thinking and enthusiasm for translating data into actionable insight to generate consistently accurate and useful analysis and models. • Excel at handling both structured and unstructured data. • Strong analytical skills and proven track record in deploying innovative SaaS solutions in the tech industry. • Attention to detail and time management delivering high-quality work for multiple projects across several engagements while meeting deadlines.