Data Scientist

The Opportunity

The Adobe Digital Media Engagement and Retention Analytics team is focused on using the power of data to understand customers, inform strategy, measure progress toward goals and uncover new opportunities. We are looking for a Data Scientist who is passionate about using big data to deliver key insights to drive critical business decisions. The ideal candidate will have hands-on experience with analytics and data science applied to subscription business, outstanding quantitative analysis and technical skills, superb communication, and experience working within a highly cross-functional ecosystem. You will focus on driving data science and analysis across a wide variety of strategic projects to improve customer engagement & retention. Put simply, this role is responsible for answering: What is going on? What should we do? This role will be focused on identifying drivers of customer engagement and retention, specifically around B2C or individual customers.

What you’ll do:

• Apply expertise in quantitative analysis, data modeling, and other data science approaches to gain deep insights into customers’ behavior and journey across surfaces impacting customer engagement and retention
• Use insights and data to inform strategies that increase customer engagement and retention
• Monitor weekly performance, understand the root causes of changes in metrics, and provide guidance on forecasts
• Partner with Finance, Product & Marketing team to build quarterly and annual plans using data science modeling
• Define and prioritize which opportunities we should pursue to increase customer engagement and retention
• Partner with various cross-functional teams (Engagement & Retention, Data Science, Finance, Product, Campaign, and Marketing) to drive business growth
• Capture, synthesize, and interpret disparate quantitative data within the context of business objectives, identify trends, and explore data through segments and cohorts

What you’ll need to succeed:

• 6+ years of hands-on experience doing quantitative analysis preferably in the field of e-commerce, strategy, or management consulting. MS in Analytics or similar degree preferred
• Experience in defining a business problem, collecting required data, analyzing the results, and synthesizing a compelling argument
• Strong analytical skills to articulate key business and financial implications/business impact
• Strong proficiency in querying and manipulating large data sets using SQL like languages (Hive/Hadoop preferred), Python, R, etc.
• Statistical Modeling in Microsoft Excel or Power Pivot
• Experience with data visualization tools such as Tableau/Power BI
• Understanding of statistical modeling, machine learning, or data mining concepts, and a record of solving problems with these methods
• Comfortable presenting insights and findings to a broad range of stakeholders, team members, and regional partners. Ability to tell data driven stories in a clear and concise narrative
• A solid sense of self and a great sense of humor.
• Willingness and desire to lead and build new things

Our compensation reflects the cost of labor across several  U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $107,900 -- $188,300 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process.

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

Adobe is proud to be an Equal Employment Opportunity and affirmative action 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.