Adobe

Staff Data Scientist

San Jose, CA US
USD 145k - 276k
R SQL Spark Machine Learning Python Pandas
Description

Our Company

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!


 

The opportunity

Do you love to tackle complex business problems and use data to find the signal in the noise? Join the Product and Customer Analytics team at Adobe! We are a high-impact, high-visibility team well-suited to individuals with a highly quantitative, inquisitive bent of mind. We use data science to quantify and optimize the product experience for our customers! The ideal candidate will be able to work autonomously and will have a strong technical background with great communication and project management skills.

You will use data to help product, marketing and engineering teams achieve operational and execution efficiencies. Your success is predicated on finding opportunities and providing insights that enable our enterprise business to lower customer churn, increase user engagement, and facilitate product-led growth. 

We are looking for a Staff Data Scientist to improve the adoption and utilization of all our Experience Cloud products. The opportunity is huge, ranging from crafting experiments, and building machine learning models to developing new product features. We need a creative self-started who is passionate about data and has an established track record in using data science to enhance customer experience.

What you will do

In collaboration with a multi-functional group of product managers, marketers, and software developers, you will tap into the underlying clickstream data, align on metrics, and generate insights to develop valuable, highly effective programs for Adobe’s Experience Cloud products. 

You will analyze data to measure changes in user engagement which are key drivers of customer growth and retention. You will work closely with causal inference and machine learning leaders experts to measure the impacts of new product features and user engagement programs or drive in-product personalization. You will also work with data engineers to automate data pipelines to and scale experimentation and user analytics. You will build relationships across the Experience Cloud business unit to promote our team’s capabilities and tools and drive impact.

What you need to succeed

  • Experience with building and deploying Machine Learning models on platform like Databricks
  • Strong understanding of Statistics & Hypothesis Testing
  • 10+ years of work experience in data science or another related field
  • Strong Proficiency with statistical programming software like Python (pandas, scikit-learn) and/or R (dplyr, ggplot2) 
  • Experience in querying, manipulating, and analyzing large data sets using SQL and/or SQL-like languages. 
  • Experience working with Data Engineers to setup ETL/ Data Pipelines and Automate projects
  • Ability to slice & dice data, translate analysis results into insights, and present business recommendations to partners
  • Ability to identify business opportunities and dissect them from different angles, and you know how to connect the dots and interact with people in various roles and functions 
  • Communicate effectively and manage relationships with partners coming from both technical and non-technical backgrounds
  • Ability to work with multi-functional teams and juggle through parallel priorities
  • Ability to work in an ambiguous environment with strong problem-solving skills

Nice to have

  • Proficient in using Apache Spark for big data processing and analytics
  • Good understanding of experimental design and measurement (A/B Testing)
  • Familiarity with Web Analytics / Clickstream data 
  • Knowledge of B2B analytics or B2B customer lifecycle 

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 $145,600 -- $276,400 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 will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.

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.
 

Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call (408) 536-3015.

Adobe values a free and open marketplace for all employees and has policies in place to ensure that we do not enter into illegal agreements with other companies to not recruit or hire each other’s employees.

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