# Applied ML Scientist, New Grad

**Company:** [SentiLink](https://hotfix.jobs/companies/sentilink)
**Location:** Remote
**Role:** ML Engineering
**Salary:** $180k – $220k/yr
**Skills:** Python, Machine Learning, Statistics, applied data science, Postgres, AWS, amazon ec2, amazon s3, amazon rds, amazon redshift, feature engineering, Fraud Detection, identity verification, model monitoring, Data Analysis
**Posted:** 2026-08-13

> Build and deploy production machine-learning models for fraud detection, identity verification, and financial risk products. The role suits new PhD graduates or early-career researchers with strong quantitative foundations, Python experience, and interest in owning the full ML lifecycle.

## Job Description

## Responsibilities
- Develop and maintain fraud detection models through the full model development lifecycle, including data acquisition, featurization, labeling, training, experimentation, productionization, and monitoring.
- Build foundational models for Fraud and Financial Risk products.
- Research new types of fraud and develop identity verification products.
- Integrate new data sources and create inventive features through iterative research and development.
- Write production-ready code for real-time decision-making.
- Design, perform, and present analyses informing data acquisition, product development, risk operations, marketing, and sales.
- Collaborate with engineering, risk operations, and data acquisition teams to access data, maintain data quality, and support data access.

## Requirements
- Bachelor's, Master's, or PhD in Statistics, Computer Science, Physics, Mathematics, a related quantitative field, or equivalent experience/research.
- Strong foundation in machine learning, statistics, or applied data science.
- Experience with Python and common data science tools through coursework, research, internships, or personal projects.
- Ability to analyze complex problems and build data-driven solutions.
- Strong communication skills and ability to explain technical ideas clearly.
- Interest in fraud, identity, and financial risk systems.
- Ability to write clean, maintainable code.
- Strong attention to detail and curiosity about real-world data problems.
- Legal authorization to work in the United States and residence in the United States.
- Ability to thrive in a fast-paced environment solving varied, high-impact, open-ended problems.

## Compensation and Benefits
- Salary: **$180,000–$220,000 per year**, plus equity and benefits.
- Employer-paid group health insurance for employees and dependents.
- 401(k) plan with employer match.
- Flexible paid time off.
- Regular company-wide in-person events.
- Home office stipend.

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