Adobe-posted 7 days ago
$109,000 - $192,400/Yr
Full-time • Mid Level
San Jose, CA
5,001-10,000 employees

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! About the Role: Do you enjoy solving business problems and uncovering insights from data? Join the Product Data Science team within Adobe Experience Cloud! We are a high-impact group that applies machine learning and advanced analytics to help product, marketing, and engineering teams improve how customers realize value from Adobe’s enterprise products. This role is ideal for someone who’s curious, quantitative, and eager to grow as a data scientist while working on meaningful problems.

  • 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.
  • 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.
  • Strong problem-solving and critical-thinking skills, with the ability to work rigorously through ambiguity and make sound technical decisions.
  • Collaborative approach and effective communication skills, being able to translate complex technical results into clear insights and work closely with cross-functional partners.
  • 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).
  • 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).
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