Quantitative Scientist, PhD New Grad
S
SentiLinkFinancial Technology
Remote within the United StatesFull-TimeEntry
Salary$120,000/year - $220,000/year + equity + benefits
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Job Details
- Required Skills
- AWSPostgreSQLPythonMachine LearningData science
Requirements
- 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
- Thrive in a fast paced environment characterized by the need to solve extremely varied, high impact, open ended problems
Responsibilities
- Develop and maintain SentiLink’s fraud detection models through the full model development lifespan: from data acquisition decisions through featurization, focusing labeling resources, model training, experimentation, productionalization, and monitoring.
- Build foundational modeling to drive SentiLink’s expanding suite of Fraud and Financial Risk products.
- Research new types of fraud and develop new SentiLink products around identity verification.
- Achieve success by researching / developing through iteration, integration of new data sources and inventive feature engineering.
- Write production-ready code that can be relied on for real-time decision making by our partners.
- Design, perform, and present analyses that will inform data acquisition, product development, risk operations priorities, marketing, and sales efforts.
- Work with engineering, risk operations, and data acquisitions to access necessary data, maintain data quality, and support data access
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