Data Science Engineer
AdobeAbout the role
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
The Data Science team is seeking a dedicated Data Science Engineer. This role provides an outstanding opportunity to work with exceptionally skilled professionals and influence our sales strategy directly. You will be instrumental in driving business growth by successfully implementing data-driven models that identify and size potential opportunities.
You will partner with senior partners and team members to explore various data sources, engineer compelling features, then build, test, and evaluate models to prove their efficacy. Your ability to communicate complex model features to business owners will be essential for encouraging confidence and enabling sellers to drive impactful customer conversations. This is a fast-paced environment that requires the ability to make tactical decisions quickly to balance methodologies with business priorities.
What You Will Do
- Develop and own rSAM models to size headroom opportunities in the book of business for specific offerings and customer segments
- Carry out in-depth business analysis to uncover the drivers behind performance gaps and make recommendations for change
- Engage with senior collaborators to understand key growth areas and ensure solutions align with business priorities
- Assess and improve the performance of sales campaigns with performance insights and recommendations for model enhancements
- Support the customer segmentation process using rSAM and other insights
- Provide different models like customer segmentation based on clustering, customer lifetime value based on survival analysis, and forecasting
- Deliver channel segmentation to determine customer engagement strategy and optimize lifetime value
- Collaborate with data engineering teams to productionize data pipelines and drive scalable solutions
- Automate model refreshes and account prioritization processes
- Build propensity models to drive sales campaigns using predictive modelling techniques
What You Will Bring
- 5+ years of SQL experience for querying, cleansing, integrating, and summarizing complex data is essential
- Experience with Databricks and Python is desirable
- Proven experience of building, testing, evaluating, and improving revenue-generating data science models
- Knowledge of propensity modeling techniques and other modeling techniques would be beneficial
- Proven experience translating complex analytics into understandable insights for senior collaborators is essential
- Strong problem-solving skills and experience in a fast-paced business environment with changing requirements
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.
State-Specific Notices:
California:
Fair Chance Ordinances
Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and “fair chance” ordinances.
Colorado:
Application Window Notice
If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in
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