Senior ML Scientist - Fraud Detection & Impact (Hybrid)

Adobe; New York (NY); Hybrid; USD 133,000 - 236,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Adobe seeks a Senior Data Scientist (ML) to build fraud and abuse detection models and measure their effectiveness across the fraud lifecycle. You will combine hands-on modeling with experimentation, evaluation, and analytics to quantify business impact and drive improvements.

You will work across ground-truth definition, labeling approaches, and performance monitoring, crafting executive-ready insights and dashboards that translate detection results into tangible business decisions.

Qualifications

• 8+ years in applied Data Science / ML, with experience building and evaluating production ML models.
• Strong foundation in statistical and classical ML, experimentation, model evaluation, and performance measurement.
• Strong hands-on Python and SQL skills working with large, complex datasets.
• Experience with model monitoring, drift, false-positive/false-negative analysis, and imperfect or delayed labels.
• Strong data visualization and storytelling skills 22 able to translate complex analysis into clear insights and recommendations.
• Strong analytical judgment, ownership, and ability to operate independently through ambiguity.
• Bachelor's or equivalent experience in Statistics, Mathematics, Computer Science, or related field; advanced degree a plus.

Responsibilities

• Build and tune ML models for fraud and abuse detection using statistical and classical ML techniques.
• Develop robust evaluation frameworks, datasets, and metrics to measure model and mitigation effectiveness.
• Analyze false positives/negatives, model drift, and emerging fraud patterns to continuously improve detection.
• Define ground truth, labeling approaches, and fraud taxonomies that support reliable model development and evaluation.
• Design experiments and evaluate tradeoffs across precision, recall, customer impact, and fraud loss.
• Build dashboards and metrics that translate detection performance into measurable business impact.
• Pressure-test models and data for leakage, bias, data-quality issues, and other sources of misleading results.
• Partner across engineering, product, policy, and risk teams to turn insights into detection improvements and business decisions.

Skills

DS/ML experience

Python & SQL

Model evaluation

Ground truth labeling

Data visualization

Analytical mindset

Bachelor\u2019s degree in STEM

Advanced degree a plus

Education

Bachelor's degree in Statistics/Mathematics/CS

Advanced degree in related field

Job description

Adobe seeks a Senior Data Scientist (ML) to build fraud and abuse detection models and measure their effectiveness across the fraud lifecycle. You will combine hands-on modeling with experimentation, evaluation, and analytics to quantify business impact and drive improvements.

You will work across ground-truth definition, labeling approaches, and performance monitoring, crafting executive-ready insights and dashboards that translate detection results into tangible business decisions.