Data Scientist

• Partner with product managers, marketers, and engineers to analyze clickstream and product usage data.
• Develop and implement techniques to transform raw data into meaningful insights using programming languages (Python/R) and visualization tools.
• Apply statistical analysis and data mining to structured and unstructured datasets; support efforts in natural language processing and machine learning where relevant.
• Contribute to building predictive models and scalable algorithms on large-scale datasets to solve business problems.
• Assist with experimentation and measurement of new product features and user engagement programs (e.g., A/B testing, causal inference).
• Collaborate with data engineers to access, prepare, and automate datasets and pipelines for analysis. Share findings through clear visualizations and presentations to both technical and non-technical audiences.
• Learn and grow by working alongside senior data scientists on advanced projects in causal inference, personalization, and predictive modeling.

Do you enjoy solving business problems and uncovering insights from data? Join the Product and Customer Analytics team at Adobe! We are a high-impact team that uses data science and analytics to improve the product experience for our customers. This role is well-suited to someone who is curious, quantitative, and excited to apply data skills to real-world problems. You'll use data to support product, marketing, and engineering teams in driving customer engagement, retention, and growth. This role is a great opportunity to build experience in data science, work with large-scale datasets, and learn from senior data scientists and engineers., * Master's degree in a quantitative field (e.g., Statistics, Computer Science, Data Science, Engineering, or related).

• 2+ years of relevant work experience in data science, analytics, or related fields (internships and research experience count).
• Proficiency with Python (pandas, scikit-learn, matplotlib/seaborn) and/or R.
• Experience writing SQL to query and analyze data.
• Solid foundation in statistics (e.g., hypothesis testing, regression, experimental design).
• Ability to translate data analysis into clear insights and communicate them effectively.
• Curiosity, problem-solving mindset, and willingness to learn new tools and methods., * Exposure to natural language processing, unstructured data analytics, or applied econometrics.
• Familiarity with causal inference methods and A/B testing design.
• Experience with big data tools (e.g., Spark, Databricks).
• Familiarity with customer lifecycle analytics, especially in B2B contexts.
• Hands-on experience with data visualization tools (e.g., Tableau, Power BI, Looker).

Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more.

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