Quantitative Scientist, PhD New Grad

SentiLink

Quantitative Scientist building production machine-learning models for SentiLink’s identity and fraud-risk solutions. Researching fraud, engineering features, and deploying real-time models across the full ML lifecycle.

Posted 8/8/2026full-timeRemote • 🇺🇸 United StatesEntry Level💰 $120,000 - $220,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in developing and maintaining fraud detection models, with a strong foundation in machine learning and statistics. Proficient in Python and data science tools, capable of delivering data-driven solutions and collaborating effectively across teams.

Highest-signal resume keywords

Machine LearningPython ProgrammingData Science ToolsFraud Detection ModelsStatistical Analysis

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatisticsData AnalysisFeature EngineeringModel Development LifecycleReal-Time Decision-MakingData AcquisitionProduction-Ready CodeIdentity VerificationData Quality Maintenance

Soft Skills

Strong Communication SkillsAttention to DetailCuriosityProblem-SolvingAbility to Thrive in Fast-Paced Environment

Industry Keywords

FraudFinancial RiskData-Driven SolutionsRisk OperationsData Access

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Develop and maintain fraud detection models through the full model development lifecycle, from data acquisition and feature engineering through training, production deployment, and monitoring
Build foundational models for Fraud and Financial Risk products
Research new types of fraud and develop identity verification products
Iterate on models and integrate new data sources and inventive feature engineering
Write production-ready code for real-time decision-making by partners
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

What you’ll need

Bachelor’s, Master’s, or PhD in Statistics, Computer Science, Physics, Mathematics, or 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
Demonstrated ability to analyze complex problems and build data-driven solutions
Strong communication skills and ability to explain technical ideas clearly
Interest in learning deeply about fraud, identity, and financial risk systems
Ability to write clean, maintainable code
Strong attention to detail and curiosity about real-world data problems
Legally authorized to work in the United States
Must live in the United States
Ability to thrive in a fast-paced environment solving varied, high-impact, open-ended problems

Benefits

Comp & perks

Employer paid group health insurance for you and your dependents
401(k) plan with employer match
Flexible paid time off
Regular company-wide in-person events
Home office stipend