Senior AI/ML Fraud Strategist / Data Scientist

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

As a Computer Scientist on the Fraud Team, you will be responsible for spearheading the development and execution of an innovative Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP) strategy to combat various fraudulent activities, including bot attacks, Account Takeover (ATO) incidents, phishing schemes, theft, and product misuse.

What You’ll Do

You will apply your expertise in computational analysis to design sophisticated algorithms that identify patterns of fraud and abuse effectively. This role involves researching the latest advancements in AI and ML to maintain the robustness of our fraud detection systems. Your work will contribute to the development of real-time solutions that protect our users and ensure the integrity of our platform. Collaborating closely with other data scientists, security experts, and software engineers, you will help shape a secure digital environment. This position is a unique opportunity to utilize cutting-edge technology to confront online fraudulent activity.

What You Need to Succeed

• Bachelors in Computer Science, Data Science, or a related field; Masters preferred.
• 7-10 years of Data Science experience
• A minimum of 3 years of experience in developing AI, ML, DL, and NLP algorithms, with a particular focus on fraud detection and prevention.
• Proven track record of successful implementation of AI-based strategies to combat online fraud and abuse.
• Deep understanding of online fraud activity, including bots, ATOs, phishing, theft, and misuse.
• Proficiency in programming languages such as Python, R, Java, or similar.
• Strong problem-solving skills and ability to think critically and innovatively.
• Excellent communication and teamwork skills for effective cross-functional collaboration.
• Ability to stay updated with the latest research and trends in AI, ML, DL, NLP, and cybersecurity.
• Experience with big data technologies and tools, such as Databricks, Hadoop, Spark, etc., is a plus.

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 $140,200 -- $261,400 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 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.

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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.