# Senior Data Scientist, ML— Fraud Detection & Effectiveness

**Company**: Adobe
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $133,100 - $236,400 annually
**Category**: Data Science
**Industry**: Technology

**Apply**: https://adobe.wd5.myworkdayjobs.com/en-US/external_experienced/job/San-Jose/Senior-Data-Scientist--ML--Fraud-Detection---Effectiveness_R171806-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_62814a85-738

## Description

We are seeking an experienced Senior Machine Learning Data Scientist to build fraud and abuse detection models and measure how effectively they work. This role combines hands-on modeling with deep experimentation, evaluation, and analytics to improve detection and quantify business impact.

You will work across the fraud lifecycle , from modeling and ground-truth definition to performance measurement, monitoring, and executive-ready insights!

**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.

**Requirements**

- 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 , 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.

**Preferred Attributes**

- Experience in fraud, abuse, risk, identity, trust & safety, or other adversarial domains.

- Experience with anomaly detection, clustering, behavioral modeling, or prevalence estimation.

- Experience with labeling frameworks, weak supervision, active learning, or human-review systems.

- Familiarity with LLMs and AI-assisted evaluation/analysis.

- Experience evaluating multi-layered risk controls and automated decisioning systems.

**Hybrid Work Model**: This role follows a hybrid schedule, with a minimum of 3 days per week in the office.

**Expected Pay Range**: The U.S. pay range for this position is $133,100 - $236,400 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience.

## Skills

### Required
- Python
- SQL
- Machine Learning
- Data Science
- Statistical Analysis
- Data Visualization

### Nice to have
- Anomaly Detection
- Clustering
- Behavioral Modeling
- Prevalence Estimation
- Labeling Frameworks
- Weak Supervision
- Active Learning
- Human-Review Systems
- LLMs
- AI-assisted Evaluation/Analysis

---

Source: [Apply at adobe.wd5.myworkdayjobs.com](https://adobe.wd5.myworkdayjobs.com/en-US/external_experienced/job/San-Jose/Senior-Data-Scientist--ML--Fraud-Detection---Effectiveness_R171806-1?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)