Changing the world through digital experiences is what Adobe’s all about. They give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! They’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.
Adobe’s on a mission to hire the very best and is committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. They realize that new ideas can come from everywhere in the organization, and they know the next big idea could be yours!
The Adobe XD and CC Web Data Science Team is looking for a Senior Data Scientist who is passionate about data and has the desire to provide a delightful product experience for the customers. Using extensive product usage data sets, you will partner directly with product managers, product marketing managers, and software engineers to harness the data, derive significant insights, and help lay the foundation for robust and reliable data-centric decision-making. You will have the opportunity to focus on new and intriguing initiatives spanning, product analytics, dashboards, data engineering, GTM analytics, growth, and more. Your primary focus will be to develop and maintain a modern data architecture to advance the reporting capabilities, analytics, and experimentation capabilities, and on a longer term you will use predictive modeling and machine learning methods to allow the broader organization to understand, lead, and optimize the customer experiences. Join the innovative team and make an impact in the most exiting areas of Adobe!
- Partner with product and engineering teams to understand existing product instrumentation and help bridge gaps in data streams to assist data science initiatives.
- Analyze usage patterns to better understand customer behavior including acquisition, engagement, conversion, and retention.
- Proactively identify customer trends and communicate relevant insights to assist product decision-making.
- Automate and optimize data pipelines using SQL and/or Python-based ETL Frameworks.
- Build and maintain various product and engineering dashboards to advise the team about the state of the business, as well as to alert business partners when issues occur.
- Architect and implement models to recommend personalized in-app content.
- Drive A/B and multivariate tests and design of feature-level experiments to validate hypotheses and influence product development decisions.
- MS or Ph.D. in data science, computer science, statistics, applied mathematics, engineering, or economics.
- 5 – 7+ years of relevant data science experience.
- Experience translating business questions into data analytics approaches.
- Strong proficiency in querying and manipulating large datasets using SQL-like languages (Hive, Spark, etc.).
- Experience developing and operationalizing consistent approaches to experimentation, using appropriate statistical techniques to reduce bias and interpret statistical significance.
- Strong proficiency with descriptive and inferential statistics (i.e. t-test, chi-square, ANOVA, correlation, regression, etc.) to understand customer engagement and generate hypotheses.
- Strong proficiency building machine learning algorithms and pipelines using Python or R.
- Experience crafting data visualizations and storytelling to efficiently communicate analysis results to both technical and non-technical audiences.
- Knowledge of relevant tools in this field such as Hadoop, Hive, Splunk, Spark, Tableau, Excel (Charting and Pivot-Tables), and Power BI.
- Experience in product instrumentation is a plus.
- Possess natural curiosity and technical competence, being capable of asking critical questions and always ready to address any challenges.
- Experience addressing an executive level audience.
- Excellent communication, relationship skills, and a strong teammate.
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1