Quantitative Scientist, PhD New Grad

Ovii's Interpretation of the Role

SentiLink seeks a Quantitative Scientist to design, build, and ship machine‑learning models that detect fraud and assess financial risk. The position is remote‑first within the United States and is aimed at new PhD graduates or early‑career researchers eager to apply data science to real‑world identity‑verification problems.

Role Snapshot

• Full‑stack data science role
• End‑to‑end ML model ownership
• Focus on fraud detection & financial risk
• Remote (U.S.) with office preference in Austin, SF, NY
• Early‑career / new‑grad opportunity

Must-Have Requirements

• Python
• Machine learning
• Statistics
• Data‑science tools (e.g., pandas, scikit‑learn)
• PostgreSQL
• AWS cloud services
• Clean, maintainable code
• Strong communication
• machine learning model development
• fraud detection research
• full‑stack data science
• Bachelor’s, Master’s, or PhD in Statistics, Computer Science, Physics, Mathematics, or related quantitative field
• must be legally authorized to work in the United States
• must live in the United States

Work Setup

• Location: United States
• Work mode: REMOTE
• Remote scope: COUNTRY_RESTRICTED
• Remote countries: United States
• Employment type: Full-Time

Eligibility Gates

• Work authorization: must be legally authorized to work in the United States
• Visa sponsorship: no

Not Specified in JD

• Travel
• Security clearance

What You'll Likely Work On

• Develop, train, and monitor fraud‑detection models across the full ML lifecycle
• Create foundational models for expanding fraud and financial‑risk product suite
• Research emerging fraud patterns and translate findings into new identity‑verification products
• Engineer feature pipelines and integrate novel data sources for improved model performance
• Write production‑grade code that powers real‑time decision APIs
• Design and present analyses that guide data acquisition, product roadmap, risk operations, marketing, and sales
• Partner with engineering, risk‑operations, and data‑acquisition teams to ensure data quality and accessibility

Good Fit If You Have

• Strong curiosity about fraud, identity, and financial‑risk systems
• Thrives in fast‑paced, high‑impact problem solving
• Enjoys collaborating across product, engineering, and risk teams