Adobe is looking to solve business problems and uncover insights from data to improve how customers realize value from Adobe's enterprise products
Requirements
Proficiency in Python and SQL, with hands-on experience in data manipulation and applied machine learning using libraries such as Pandas, NumPy, Scikit-learn, and Matplotlib/Seaborn
Proven ability in designing and implementing scalable data and feature pipelines using distributed frameworks such as Spark or Databricks, ensuring data quality, performance, and reproducibility
Strong foundation in statistics and experimental design, including hypothesis testing, regression, and model evaluation
Ability to apply software-engineering standards; modular, well-documented code, version control (Git), reproducible workflows, and testing for model and data quality
Familiarity with NLP, LLMs or Generative AI, including embeddings, topic modeling, prompt engineering, or retrieval-augmented generation (RAG)
Exposure to MLOps and workflow practices that support scalable, reliable analytics and model deployment (model versioning, monitoring, automation)
Strong problem-solving and critical-thinking skills, with the ability to work rigorously through ambiguity and make sound technical decisions
Responsibilities
Design, build and productionize machine-learning models that generate insights, segment users, predict outcomes, and drive measurable business impact
Analyze product usage and customer datasets to uncover behavioral patterns, feature adoption trends, and growth opportunities
Build and maintain robust data workflows that clean, transform, and validate structured and unstructured data using scalable tools and platforms (such as Databricks, Spark or similar)
Develop reproducible codebases, notebooks, and utilities that improve efficiency, consistency, and collaboration across analytics and ML projects
Practice and promote strong data practices, including transparency, version control, reproducibility, and compliance with governance and security requirements
Visualize and communicate analytical results clearly, presenting findings and recommendations that enable partners to make data-driven decisions
Collaborate cross-functionally with product managers, marketers, engineers, and other data scientists to define data science questions, develop solutions, validate outcomes, and translate results into actionable insights
Other
4+ years of relevant experience in data science or related technical roles, preferably within applied machine learning or product data science environments
Postgraduate degree or equivalent experience in a quantitative field (such as Statistics, Computer Science, Data Science, Engineering, or related field)
Collaborative approach and effective communication skills, being able to translate complex technical results into clear insights and work closely with cross-functional partners
Ability to work in a team environment and contribute to the development of a positive and inclusive team culture
Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and fair chance ordinances
