Data Science Engineer, Payment Risk

Our Company

Changing the world through digital experiences is what Adobes all about. We give everyonefrom emerging artists to global brandseverything they need to design and deliver exceptional digital experiences! Were passionate about empowering people to create beautiful and powerful images videos and apps and transform how companies interact with customers across every screen.

Were 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

Adobe is building a global payments function and recruiting a seasoned payment risk specialist to join our team dedicated to managing payment fraud and related risks. You will bring both risk strategy experience from an online merchant and deep analytical capabilities to this role. Your ability to pull and analyze data will help you find ways to improve risk decisioning at checkout. This will allow you to block BOT attacks and prevent fraudulent transactions. Youll balance the sensitive ratio of false positives to false negatives and evolve prevention strategies to drive Adobes business objectives. You will help define payment risk policies and build programs that prevent detect identify and resolve fraudulent activity by customers potential customers and outside agents. You will support outreach programs to the large issuing banks around the world to influence how they decision Adobe transactions. You will define A/B tests and monitor performance with a control group. This improves how you identify false positives globally using statistical methods to enable better decision-making.

What Youll Do

• Mitigate fraudulent payment activity involving credit/debit cards SEPA PayPal and other payment methods worldwide. Collaborate with Adobes third-party risk assessment partner and internal ML team.
• Partner closely with internal collaborator organizations across Adobe including Risk/Abuse team Chargeback team ML Decisioning Engineers Product Management Payments Partnerships and Finance.
• Establish Fraud Prevention capabilities based on predictive decisioning models that you will build and maintain for Adobe to align with industry best-practices.
• Implement improvements that raise the barriers against new threats by influencing the revision of business processes and decision-making capabilities and through detailed auditing and validation of these processes following implementation of these changes.
• Bring a disciplined analytical and methodical approach to a space that can be highly reactionary and chaotic from the ever evolving fraudulent attacks in the online space.
• Define and manage risk control measurements implement quantitative monitoring metrics and align internal risk teams and external risk decisioning providers on risk control numeric goals promote results-focused data-driven data science practices.
• Experiment experimental build & hypothesis testing control groups

What you need to succeed

• Hands-on experience (risk industry) with deep technical fluency and practical experience building and operating analytic systems:
• Strong hands-on SQL and Python skills Youll be writing queries building data pipelines debugging code and driving insights from large complex datasets. Proficiency in both SQL and Python is essential to operate effectively in this role (SQL/Python is a MUST).
• You should have practical experience in overseeing payment risk fraud or abuse operations. Direct knowledge of developing implementing and revising risk strategies in these areas is essential. Background in Payment Risk Fraud or Abuse is a plus. This includes driving fraud detection logic tuning decision engines and managing false positive/negative trade-offs.
• Practical machine learning experience A solid track record applying machine learning in production including model development validation deployment or serving infrastructure is a strong plus. You should be comfortable operationalizing models interpreting results and partnering with ML/engineering teams to integrate models into risk decisioning workflows.
• In addition to these core requirements successful candidates will demonstrate:
• A data-driven approach with the ability to translate analytical outcomes into business decisions and operational controls.
• The ability to influence teams across multiple functions and partner with product engineering and external risk providers.
• Comfort with defining performance metrics A/B tests and control-group experiments in a global payments environment.

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:

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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 Pacific Time in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location no specific application window applies and the posting may close at any time based on hiring needs.

Massachusetts:

Massachusetts Legal Notice

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

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