Applied Scientist, PhD New Grad

SentiLink

Applied Scientist building production fraud-detection models for SentiLink’s identity-risk solutions. Researching fraud, engineering features, and deploying real-time machine-learning systems.

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

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and maintaining fraud detection models, utilizing machine learning and statistical analysis to create data-driven solutions. Proficient in Python and data science tools, with a strong focus on collaboration and communication across teams to enhance fraud and financial risk products.

Highest-signal resume keywords

Machine LearningPython ProgrammingData AnalysisFraud DetectionStatistical Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatistical AnalysisData ScienceFeature EngineeringModel DevelopmentProduction-Ready CodeData AcquisitionReal-Time Decision-MakingData Quality MaintenanceProblem Solving

Soft Skills

Strong CommunicationAttention to DetailCuriosityCollaborationAdaptability

Tools & Technologies

Data Science ToolsStatistical SoftwarePython Libraries

Industry Keywords

FraudFinancial RiskIdentity VerificationData-Driven SolutionsQuantitative Analysis

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, experimentation, productionization, and monitoring
Build foundational models for Fraud and Financial Risk products
Research new types of fraud and develop identity-verification products
Iterate on research and development, integrate new data sources, and perform 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 necessary data, maintain data quality, and support data access
Own a respective technical domain and work on high-visibility, high-impact projects
Collaborate across the company to research fraud, develop products, and provide analysis

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 involving varied, high-impact, open-ended problems

Benefits

Comp & perks

Equity
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